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[{"$f":"ROW()&\")\"","v":"1)"},"When you multiply or Divide Decimals AND you are required to Round your answer AND you will use the calculation in subsiquent formulas, you must use the ROUND function"]
[{"$f":"ROW()&\")\"","v":"2)"},"The second argument in the ROUND function:  0 means round to the ones position"]
[{"$f":"ROW()&\")\"","v":"3)"},"The second argument in the ROUND function:  2 means round to the penny"]
[{"$f":"ROW()&\")\"","v":"4)"},"The second argument in the ROUND function:  -3 means round to the thousands position"]
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[null,"Taxable Earnings","Deduction",null,"Your boss will verify if your pennies are added correctly"]
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[{"$f":"ROW()&\")\"","v":"2)"},"The second argument in the ROUND function:  0 means round to the ones position"]
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["ROUND","follows rounding rules",null,2.1560000000000001]
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["CEILING","ROUND UP TO NEARSET NUMBER OF SIGNIFICANCE (GOOD FOR PRICES)",null,685.21,null,0.5]
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[]
["Round","ROUND(23.50%,2) = 24% ==> .24",{"$f":"ROUND(D11,2)","v":0.24},0.23499999999999999]

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[null,null,null,null,null,null,null,null,"Terms of Use. © 2008 Microsoft Corporation and/or its suppliers. All rights reserved."]
[null,null,null,null,null,null,null,null,"Data providers"]
[null,null,null,null,null,null,null,null,"Canadian investment fund pricing (c) 2008 CANNEX Financial Exchanges Limited."]
[null,null,null,null,null,null,null,null,"Analyst Recommendations data provided by Zacks Investment Research."]
[null,null,null,null,null,null,null,null,"Fund data provided by Morningstar, Inc. © 2008. All rights reserved."]
[null,null,null,null,null,null,null,null,"Copyright © 2008 Reuters. Click for Restrictions."]
[null,null,null,null,null,null,null,null,"Quotes supplied by ComStock, an Interactive Data company."]
[null,null,null,null,null,null,null,null,"StockScouter data provided by Gradient Analytics, Inc."]

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[null,null,null,null,null,null,null,null,"Analyst Recommendations data provided by Zacks Investment Research."]
[null,null,null,null,null,null,null,null,"Fund data provided by Morningstar, Inc. © 2008. All rights reserved."]
[null,null,null,null,null,null,null,null,"Copyright © 2008 Reuters. Click for Restrictions."]
[null,null,null,null,null,null,null,null,"Quotes supplied by ComStock, an Interactive Data company."]
[null,null,null,null,null,null,null,null,"StockScouter data provided by Gradient Analytics, Inc."]

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[{"$f":"ROW()&\")\"","v":"1)"},"We calculate the mean (add up and divide by the count) using the AVERAGE function so that we can have 1 number that represents all the data points! "]
[{"$f":"ROW()&\")\"","v":"2)"},"But how do we know whether our mean represents all the data points fairly? Is it a good mean? Measuring the variation in the data points will tell us whether our mean is a good mean!"]
[{"$f":"ROW()&\")\"","v":"3)"},"We will look at the functions STDEV (standard deviation for a sample), VAR (variance for a sample), and AVEDEV (mean deviation for the sample)."]
[{"$f":"ROW()&\")\"","v":"4)"},"The smaller the results from these formulas, the better the mean represents it's data points (\"it is a good mean!\")."]
[]
[null,"Sales Dept 1","Sales Dept 2",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,{"$f":"B6&\" Y values\"","v":"Sales Dept 1 Y values"},{"$f":"B6&\" Y values\"","v":"Sales Dept 1 Y values"},{"$f":"C6&\" Y values\"","v":"Sales Dept 2 Y values"},{"$f":"C6&\" Y values\"","v":"Sales Dept 2 Y values"}]
[null,242,500,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,250,230,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,289,364,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,294,172,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,310,130,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,157,107,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,348,290,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,287,122,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,321,457,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,275,447,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,384.00000000000034,321,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,316,378,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,318,375,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,269,100,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,290,357,null,null,{"$f":"B6","v":"Sales Dept 1"},{"$f":"C6","v":"Sales Dept 2"},null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,null,null,null,"Variance",{"$f":"VAR(B7:B21)","v":2664.7142857143022},{"$f":"VAR(C7:C21)","v":18819.285714285714}]
[null,null,null,null,"Standard Deviation"]
[null,null,null,null,"Mean Deviation",{"$f":"AVEDEV(B7:B21)","v":34.800000000000026},{"$f":"AVEDEV(C7:C21)","v":117.2}]

{"sheet":"Ave & SD (an)","index":9,"n_rows":24,"n_cols":24,"rows_kept":24,"cut":false,"hidden":false,"merged":[]}
[{"$f":"ROW()&\")\"","v":"1)"},"We calculate the mean (add up and divide by the count) using the AVERAGE function so that we can have 1 number that represents all the data points! "]
[{"$f":"ROW()&\")\"","v":"2)"},"But how do we know whether our mean represents all the data points fairly? Is it a good mean? Measuring the variation in the data points will tell us whether our mean is a good mean!"]
[{"$f":"ROW()&\")\"","v":"3)"},"We will look at the functions STDEV (standard deviation for a sample), VAR (variance for a sample), and AVEDEV (mean deviation for the sample)."]
[{"$f":"ROW()&\")\"","v":"4)"},"The smaller the results from these formulas, the better the mean represents it's data points (\"it is a good mean!\")."]
[]
[null,"Sales Dept 1","Sales Dept 2",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,{"$f":"B6&\" Y values\"","v":"Sales Dept 1 Y values"},{"$f":"B6&\" Y values\"","v":"Sales Dept 1 Y values"},{"$f":"C6&\" Y values\"","v":"Sales Dept 2 Y values"},{"$f":"C6&\" Y values\"","v":"Sales Dept 2 Y values"}]
[null,242,500,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,250,230,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,289,364,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,294,172,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,310,130,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,157,107,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,348,290,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,287,122,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,321,457,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,275,447,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,384.00000000000034,321,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,316,378,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,318,375,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,269,100,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,290,357,null,null,{"$f":"B6","v":"Sales Dept 1"},{"$f":"C6","v":"Sales Dept 2"},null,null,null,null,null,null,null,null,null,null,null,null,null,2,3,5,6]
[null,{"$f":"AVERAGE(B7:B21)","v":290},{"$f":"AVERAGE(C7:C21)","v":290},null,"Variance",{"$f":"VAR(B7:B21)","v":2664.7142857143022},{"$f":"VAR(C7:C21)","v":18819.285714285714}]
[null,null,null,null,"Standard Deviation",{"$f":"STDEV(B7:B21)","v":51.620870640800916},{"$f":"STDEV(C7:C21)","v":137.18340174483833}]
[null,null,null,null,"Mean Deviation",{"$f":"AVEDEV(B7:B21)","v":34.800000000000026},{"$f":"AVEDEV(C7:C21)","v":117.2}]

{"sheet":"Statistics","index":10,"n_rows":167,"n_cols":43,"rows_kept":167,"cut":false,"hidden":false,"merged":[]}
["When should you name ranges? When you have data that you will refer to often. If data is in Excel Table format, Table names are very convienient."]
[]
["Why do we need averages? Because we need to have one number that will represent all the numbers in the data set. We need to have a \"typical value\" that will represent all the data points.",null,null,null,"Historical Average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"n =","total # observations",{"$f":"COUNT(Sales)","v":0},"count"]
["Mean = (add them up)/Count = Most common average = AVERAGE = ",null,null,null,5890,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"k =","# of classes",6,"type in till TRUE"]
["Median = after ranking, which is in middle (if even number, then add 2 in middle and divide by 2) = good when you don't want very large or small numbers pulling the mean up or down (think of real estate ) = MEDIAN =",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,{"$f":"2^AE4>=AE3","v":true},"2^k > = n"]
["Mode = the one that occurs most frequently (not always a mode or sometimes theer can be more than 1 mode) = this average is good when you are counting (think of prefer/notPrefer in a soft drink test - adding all the ones and dividing by the count yields 1) = MODE =",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Max",{"$f":"MAX(Sales)","v":{"$error":"#NAME?"}}]
["Why do we need Standard Deviation (a measure of variation in data)? Because we need to know if our mean represents that data points fairly!",null,null,null,null,"Historical Average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Min",{"$f":"MIN(Sales)","v":{"$error":"#NAME?"}}]
["Standard Deviation for a sample = tells you \"how good your mean is\", or \"how fairly the mean represents all the data points, or \"on average, how far away from the average is the actual data point?\", SQRT(SUM((X - Xmean)^2)/(CountOf(X - Xman) - 1)) = STDEV =",null,null,null,null,3020,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Range",{"$f":"AE6-AE7","v":{"$error":"#NAME?"}}]
["Mean Deviation = \"how good is your mean\" = SUM(ASB(X - Xmean))/(CountOf(X - Xman) - 1) = AVEDEV =",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Class Interval = (Max - Min)/k =",{"$f":"AE8/AE4","v":{"$error":"#NAME?"}}]
["Maximum = what value is the largest = MAX =",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Class Interval (always round up) =",{"$f":"CEILING(D12/AE4,500)","v":0}]
["Minimum = what value is the smallest = MAX =",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Lower Limit of first class",0]
["MAX - MIN = Range",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Upper Limit of last class",13000]
["Count # of Sales using \"numbers\" = COUNT ="]
["Count # of Sales using \"Text\", or non-empty cells = COUNTA ="]
["Skew = 1) 0 = Bell shaped ==> mean = median = mode; 2) -# = curve titled toward right ==> Mean < Median < Mode (mean pulled down by a few small numbers); +# = curve titled toward left Mean > Median > Mode (Mean is pulled up by a few large numbers)."]
[]
["Sales Total Rank Table & Bonus Total",null,null,null,"Bonus Amount",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Rank with ties receiving same value",null,null,null,"Rank with no Ties, 1st and 2nd tie get \"add 1\"",null,null,null,"Rank with no Ties, each tie gets same value"]
["Sales Rep (Category)","Toatl Sales","Rank",50000,2000,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Sales Rep (Category)","Frequency","Rank",null,"Sales Rep (Category)","Frequency","Rank",null,"Sales Rep (Category)","Frequency","Rank"]
["Al",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Al",5000,{"$f":"RANK(AH19,AH$19:AH$24,0)+COUNTIF(AH$18:AH18,AH19)","v":2},null,"Al",5000,{"$f":"RANK(AL19,AL$19:AL$24,0)+COUNTIF(AL$18:AL18,AL19)","v":2},null,"Al",5000,{"$f":"RANK(AP19,AP$19:AP$24,0)+(COUNT(AP$19:AP$24)+1-RANK(AP19,AP$19:AP$24,0)-RANK(AP19,AP$19:AP$24,1))/2","v":3}]
["Gwen",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Gwen",5000,{"$f":"RANK(AH20,AH$19:AH$24,0)+COUNTIF(AH$18:AH19,AH20)","v":3},null,"Gwen",5000,{"$f":"RANK(AL20,AL$19:AL$24,0)+COUNTIF(AL$18:AL19,AL20)","v":3},null,"Gwen",5000,3]
["Michele",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Michele",5000,{"$f":"RANK(AH21,AH$19:AH$24,0)+COUNTIF(AH$18:AH20,AH21)","v":4},null,"Michele",5000,{"$f":"RANK(AL21,AL$19:AL$24,0)+COUNTIF(AL$18:AL20,AL21)","v":4},null,"Michele",5000,3]
["Megan",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Megan",5890,{"$f":"RANK(AH22,AH$19:AH$24,0)+COUNTIF(AH$18:AH21,AH22)","v":1},null,"Megan",5890,{"$f":"RANK(AL22,AL$19:AL$24,0)+COUNTIF(AL$18:AL21,AL22)","v":1},null,"Megan",5890,1]
["Luong",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Luong",4900,{"$f":"RANK(AH23,AH$19:AH$24,0)+COUNTIF(AH$18:AH22,AH23)","v":5},null,"Luong",4900,{"$f":"RANK(AL23,AL$19:AL$24,0)+COUNTIF(AL$18:AL22,AL23)","v":5},null,"Luong",4900,5.5]
["Joel",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Joel",4900,{"$f":"RANK(AH24,AH$19:AH$24,0)+COUNTIF(AH$18:AH23,AH24)","v":6},null,"Joel",4900,{"$f":"RANK(AL24,AL$19:AL$24,0)+COUNTIF(AL$18:AL23,AL24)","v":6},null,"Joel",4900,5.5]
[]
["Number Of Sales Rank Table (Frequency Table)"]
["Sales Rep (Category)","Frequency","Relative Frequency","Rank"]
["Al"]
["Gwen"]
["Michele"]
["Megan"]
["Luong"]
["Joel"]
[null,{"$f":"SUM(B28:B33)","v":0}]
[]
["Lower limit of first class","Class interval"]
[0,2000]
["Lower Class Limit","Upper Class Limit","Class","Frequency"]
[]
[]
[]
[]
[]
[]
[]
[null,null,null,{"$f":"SUM(D39:D45)=COUNT(Sales)","v":true}]
[]
[]
["Largest Sales =",5,null,null,"Smallest Sales =",{"$f":"B49","v":5}]
["Table with 5 Largest Sales",null,null,null,"Table with 5 Largest Sales"]
["Rank","Amount","Sales Rep",null,"Rank","Amount","Sales Rep"]
[{"$f":"IF(ROW(A1)<=B$49,ROW(A1),\"\")","v":1},null,{"$f":"IF(OR(A52=\"\",B52=\"\"),\"\",INDEX(SalesReps,MATCH(B52,Sales,0)))","v":""},null,{"$f":"IF(ROW(E1)<=F$49,ROW(E1),\"\")","v":1},null,{"$f":"IF(OR(E52=\"\",F52=\"\"),\"\",INDEX(SalesReps,MATCH(F52,Sales,0)))","v":""}]
[2,null,{"$f":"IF(OR(A53=\"\",B53=\"\"),\"\",INDEX(SalesReps,MATCH(B53,Sales,0)))","v":""},null,2,null,{"$f":"IF(OR(E53=\"\",F53=\"\"),\"\",INDEX(SalesReps,MATCH(F53,Sales,0)))","v":""}]
[3,null,{"$f":"IF(OR(A54=\"\",B54=\"\"),\"\",INDEX(SalesReps,MATCH(B54,Sales,0)))","v":""},null,3,null,{"$f":"IF(OR(E54=\"\",F54=\"\"),\"\",INDEX(SalesReps,MATCH(F54,Sales,0)))","v":""}]
[4,null,{"$f":"IF(OR(A55=\"\",B55=\"\"),\"\",INDEX(SalesReps,MATCH(B55,Sales,0)))","v":""},null,4,null,{"$f":"IF(OR(E55=\"\",F55=\"\"),\"\",INDEX(SalesReps,MATCH(F55,Sales,0)))","v":""}]
[5,null,{"$f":"IF(OR(A56=\"\",B56=\"\"),\"\",INDEX(SalesReps,MATCH(B56,Sales,0)))","v":""},null,5,null,{"$f":"IF(OR(E56=\"\",F56=\"\"),\"\",INDEX(SalesReps,MATCH(F56,Sales,0)))","v":""}]
[]
["Sales","Sales Rep"]
[6660,"Megan"]
[9973,"Michele"]
[3014,"Joel"]
[1932,"Megan"]
[9548,"Megan"]
[4831,"Michele"]
[10032,"Luong"]
[12114,"Al"]
[8831,"Al"]
[12681,"Joel"]
[3980,"Luong"]
[5083,"Luong"]
[9446,"Michele"]
[6021,"Joel"]
[1745,"Gwen"]
[7855,"Megan"]
[3076,"Michele"]
[10664,"Gwen"]
[5944,"Joel"]
[9402,"Joel"]
[3212,"Megan"]
[4410,"Al"]
[9439,"Al"]
[942,"Megan"]
[12702,"Al"]
[8740,"Megan"]
[6283,"Megan"]
[6091,"Michele"]
[3859,"Megan"]
[10279,"Joel"]
[9257,"Michele"]
[9234,"Megan"]
[10256,"Megan"]
[791,"Gwen"]
[7117,"Gwen"]
[1010,"Luong"]
[5969,"Al"]
[11534,"Gwen"]
[4768,"Al"]
[12434,"Michele"]
[8201,"Joel"]
[3932,"Al"]
[915,"Michele"]
[9498,"Al"]
[8578,"Megan"]
[7973,"Joel"]
[3521,"Gwen"]
[2944,"Joel"]
[1875,"Luong"]
[7823,"Joel"]
[2276,"Al"]
[6242,"Luong"]
[6394,"Gwen"]
[1672,"Megan"]
[6699,"Al"]
[12049,"Megan"]
[5057,"Al"]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[{"$f":"IF(MOD(ROW(),10)=0,RANDBETWEEN(7899,12999),IF(MOD(ROW(),2)=0,RANDBETWEEN(1000,6000),RANDBETWEEN(250,10000)))","v":4725}]
[{"$f":"IF(MOD(ROW(),10)=0,RANDBETWEEN(7899,12999),IF(MOD(ROW(),2)=0,RANDBETWEEN(1000,6000),RANDBETWEEN(250,10000)))","v":268}]
[2721]
[723]
[10503]
[1106]
[4554]
[9915]
[4194]
[7161]
[4098]
[6312]
[2422]
[4499]
[8780]
[2365]
[4215]
[1114]
[2758]
[5956]
[1829]
[7007]

{"sheet":"Statistics (an)","index":11,"n_rows":167,"n_cols":43,"rows_kept":167,"cut":false,"hidden":false,"merged":[]}
["When should you name ranges? When you have data that you will refer to often. If data is in Excel Table format, Table names are very convienient."]
[]
["Why do we need averages? Because we need to have one number that will represent all the numbers in the data set. We need to have a \"typical value\" that will represent all the data points.",null,null,null,"Historical Average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"n =","total # observations",{"$f":"COUNT(Sales)","v":0},"count"]
["Mean = (add them up)/Count = Most common average = AVERAGE = ",null,null,{"$f":"AVERAGE(Sales)","v":{"$error":"#NAME?"}},5890,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"k =","# of classes",6,"type in till TRUE"]
["Median = after ranking, which is in middle (if even number, then add 2 in middle and divide by 2) = good when you don't want very large or small numbers pulling the mean up or down (think of real estate ) = MEDIAN =",null,null,{"$f":"MEDIAN(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,{"$f":"2^AE4>=AE3","v":true},"2^k > = n"]
["Mode = the one that occurs most frequently (not always a mode or sometimes theer can be more than 1 mode) = this average is good when you are counting (think of prefer/notPrefer in a soft drink test - adding all the ones and dividing by the count yields 1) = MODE =",null,null,{"$f":"MODE(Sales)","v":{"$error":"#NAME?"}},{"$f":"COUNTIF(Sales,D6)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Max",{"$f":"MAX(Sales)","v":{"$error":"#NAME?"}}]
["Why do we need Standard Deviation (a measure of variation in data)? Because we need to know if our mean represents that data points fairly!",null,null,null,null,"Historical Average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Min",{"$f":"MIN(Sales)","v":{"$error":"#NAME?"}}]
["Standard Deviation for a sample = tells you \"how good your mean is\", or \"how fairly the mean represents all the data points, or \"on average, how far away from the average is the actual data point?\", SQRT(SUM((X - Xmean)^2)/(CountOf(X - Xman) - 1)) = STDEV =",null,null,{"$f":"STDEV(Sales)","v":{"$error":"#NAME?"}},{"$f":"SQRT((SUM((Sales-AVERAGE(Sales))^2)/(COUNT(Sales)-1)))","v":{"$error":"#NAME?"}},3020,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Range",{"$f":"AE6-AE7","v":{"$error":"#NAME?"}}]
["Mean Deviation = \"how good is your mean\" = SUM(ASB(X - Xmean))/(CountOf(X - Xman) - 1) = AVEDEV =",null,null,{"$f":"AVEDEV(Sales)","v":{"$error":"#NAME?"}},{"$f":"SUM(ABS(Sales-AVERAGE(Sales)))/COUNT(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Class Interval = (Max - Min)/k =",{"$f":"AE8/AE4","v":{"$error":"#NAME?"}}]
["Maximum = what value is the largest = MAX =",null,null,{"$f":"MAX(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Class Interval (always round up) =",{"$f":"CEILING(D12/AE4,500)","v":{"$error":"#NAME?"}}]
["Minimum = what value is the smallest = MAX =",null,null,{"$f":"MIN(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Lower Limit of first class",0]
["MAX - MIN = Range",null,null,{"$f":"D10-D11","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Upper Limit of last class",13000]
["Count # of Sales using \"numbers\" = COUNT =",null,null,{"$f":"COUNT(Sales)","v":0}]
["Count # of Sales using \"Text\", or non-empty cells = COUNTA =",null,null,{"$f":"COUNTA(SalesReps)","v":1}]
["Skew = 1) 0 = Bell shaped ==> mean = median = mode; 2) -# = curve titled toward right ==> Mean < Median < Mode (mean pulled down by a few small numbers); +# = curve titled toward left Mean > Median > Mode (Mean is pulled up by a few large numbers).",null,null,{"$f":"SKEW(Sales)","v":{"$error":"#NAME?"}}]
[]
["Sales Total Rank Table & Bonus Total",null,null,null,"Bonus Amount",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Rank with ties receiving same value",null,null,null,"Rank with no Ties, 1st and 2nd tie get \"add 1\"",null,null,null,"Rank with no Ties, each tie gets same value"]
["Sales Rep (Category)","Total Sales","Rank",50000,2000,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Sales Rep (Category)","Frequency","Rank",null,"Sales Rep (Category)","Frequency","Rank",null,"Sales Rep (Category)","Frequency","Rank"]
["Al",{"$f":"SUMIF($B$59:$B$115,A19,Sales)","v":{"$error":"#NAME?"}},{"$f":"RANK(B19,B$19:B$24,0)","v":{"$error":"#NAME?"}},{"$f":"IF(B19>=D$18,E$18,0)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Al",5000,{"$f":"RANK(AH19,AH$19:AH$24,0)+COUNTIF(AH$18:AH18,AH19)","v":2},null,"Al",5000,{"$f":"RANK(AL19,AL$19:AL$24,0)+COUNTIF(AL$18:AL18,AL19)","v":2},null,"Al",5000,{"$f":"RANK(AP19,AP$19:AP$24,0)+(COUNT(AP$19:AP$24)+1-RANK(AP19,AP$19:AP$24,0)-RANK(AP19,AP$19:AP$24,1))/2","v":3}]
["Gwen",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Gwen",5000,{"$f":"RANK(AH20,AH$19:AH$24,0)+COUNTIF(AH$18:AH19,AH20)","v":3},null,"Gwen",5000,{"$f":"RANK(AL20,AL$19:AL$24,0)+COUNTIF(AL$18:AL19,AL20)","v":3},null,"Gwen",5000,3]
["Michele",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Michele",5000,{"$f":"RANK(AH21,AH$19:AH$24,0)+COUNTIF(AH$18:AH20,AH21)","v":4},null,"Michele",5000,{"$f":"RANK(AL21,AL$19:AL$24,0)+COUNTIF(AL$18:AL20,AL21)","v":4},null,"Michele",5000,3]
["Megan",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Megan",5890,{"$f":"RANK(AH22,AH$19:AH$24,0)+COUNTIF(AH$18:AH21,AH22)","v":1},null,"Megan",5890,{"$f":"RANK(AL22,AL$19:AL$24,0)+COUNTIF(AL$18:AL21,AL22)","v":1},null,"Megan",5890,1]
["Luong",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Luong",4900,{"$f":"RANK(AH23,AH$19:AH$24,0)+COUNTIF(AH$18:AH22,AH23)","v":5},null,"Luong",4900,{"$f":"RANK(AL23,AL$19:AL$24,0)+COUNTIF(AL$18:AL22,AL23)","v":5},null,"Luong",4900,5.5]
["Joel",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Joel",4900,{"$f":"RANK(AH24,AH$19:AH$24,0)+COUNTIF(AH$18:AH23,AH24)","v":6},null,"Joel",4900,{"$f":"RANK(AL24,AL$19:AL$24,0)+COUNTIF(AL$18:AL23,AL24)","v":6},null,"Joel",4900,5.5]
[]
["Number Of Sales Rank Table (Frequency Table)"]
["Sales Rep (Category)","Frequency","Relative Frequency","Rank"]
["Al",{"$f":"COUNTIF($B$59:$B$115,A28)","v":12},{"$f":"B28/B$34","v":0.21052631578947367},{"$f":"RANK(B28,B28:B33,0)","v":2}]
["Gwen",7,0.12280701754385964,5]
["Michele",8,0.14035087719298245,4]
["Megan",14,0.24561403508771928,{"$f":"RANK(B31,B31:B38,0)","v":{"$error":"#NAME?"}}]
["Luong",6,0.10526315789473684,{"$f":"RANK(B32,B32:B39,0)","v":{"$error":"#NAME?"}}]
["Joel",10,0.17543859649122806,{"$f":"RANK(B33,B33:B40,0)","v":{"$error":"#NAME?"}}]
[null,{"$f":"SUM(B28:B33)","v":57}]
[]
["Lower limit of first class","Class interval"]
[0,{"$f":"AE10","v":{"$error":"#NAME?"}}]
["Lower Class Limit","Upper Class Limit","Class","Frequency"]
[{"$f":"A37","v":0},{"$f":"A39+B$37","v":{"$error":"#NAME?"}},{"$f":"DOLLAR(A39,0)&\" up to \"&DOLLAR(B39,0)","v":{"$error":"#NAME?"}},{"$f":"COUNTIF(Sales,\"<\"&B39)-COUNTIF(Sales,\"<\"&A39)","v":{"$error":"#NAME?"}}]
[{"$f":"B39","v":{"$error":"#NAME?"}},{"$f":"A40+B$37","v":{"$error":"#NAME?"}},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$f":"B40","v":{"$error":"#NAME?"}},{"$f":"A41+B$37","v":{"$error":"#NAME?"}},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[null,null,null,{"$f":"SUM(D39:D45)=COUNT(Sales)","v":{"$error":"#NAME?"}}]
[]
[]
["Largest Sales =",5,null,null,"Smallest Sales =",5]
["Table with 5 Largest Sales",null,null,null,"Table with 5 Largest Sales"]
["Rank","Amount","Sales Rep",null,"Rank","Amount","Sales Rep"]
[{"$f":"IF(ROW(A1)<=B$49,ROW(A1),\"\")","v":1},{"$f":"IF(A52=\"\",\"\",LARGE(Sales,A52))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A52=\"\",B52=\"\"),\"\",INDEX(SalesReps,MATCH(B52,Sales,0)))","v":{"$error":"#NAME?"}},null,{"$f":"IF(ROW(E1)<=F$49,ROW(E1),\"\")","v":1},{"$f":"IF(E52=\"\",\"\",SMALL(Sales,E52))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(E52=\"\",F52=\"\"),\"\",INDEX(SalesReps,MATCH(F52,Sales,0)))","v":{"$error":"#NAME?"}}]
[2,{"$f":"IF(A53=\"\",\"\",LARGE(Sales,A53))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A53=\"\",B53=\"\"),\"\",INDEX(SalesReps,MATCH(B53,Sales,0)))","v":{"$error":"#NAME?"}},null,2,{"$f":"IF(E53=\"\",\"\",SMALL(Sales,E53))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(E53=\"\",F53=\"\"),\"\",INDEX(SalesReps,MATCH(F53,Sales,0)))","v":{"$error":"#NAME?"}}]
[3,{"$f":"IF(A54=\"\",\"\",LARGE(Sales,A54))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A54=\"\",B54=\"\"),\"\",INDEX(SalesReps,MATCH(B54,Sales,0)))","v":{"$error":"#NAME?"}},null,3,{"$f":"IF(E54=\"\",\"\",SMALL(Sales,E54))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(E54=\"\",F54=\"\"),\"\",INDEX(SalesReps,MATCH(F54,Sales,0)))","v":{"$error":"#NAME?"}}]
[4,{"$f":"IF(A55=\"\",\"\",LARGE(Sales,A55))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A55=\"\",B55=\"\"),\"\",INDEX(SalesReps,MATCH(B55,Sales,0)))","v":{"$error":"#NAME?"}},null,4,{"$f":"IF(E55=\"\",\"\",SMALL(Sales,E55))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(E55=\"\",F55=\"\"),\"\",INDEX(SalesReps,MATCH(F55,Sales,0)))","v":{"$error":"#NAME?"}}]
[5,{"$f":"IF(A56=\"\",\"\",LARGE(Sales,A56))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A56=\"\",B56=\"\"),\"\",INDEX(SalesReps,MATCH(B56,Sales,0)))","v":{"$error":"#NAME?"}},null,5,{"$f":"IF(E56=\"\",\"\",SMALL(Sales,E56))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(E56=\"\",F56=\"\"),\"\",INDEX(SalesReps,MATCH(F56,Sales,0)))","v":{"$error":"#NAME?"}}]
[]
["Sales","Sales Rep"]
[6660,"Megan"]
[9973,"Michele"]
[3014,"Joel"]
[1932,"Megan"]
[9548,"Megan"]
[4831,"Michele"]
[10032,"Luong"]
[12114,"Al"]
[8831,"Al"]
[12681,"Joel"]
[3980,"Luong"]
[5083,"Luong"]
[9446,"Michele"]
[6021,"Joel"]
[1745,"Gwen"]
[7855,"Megan"]
[3076,"Michele"]
[10664,"Gwen"]
[5944,"Joel"]
[9402,"Joel"]
[3212,"Megan"]
[4410,"Al"]
[9439,"Al"]
[942,"Megan"]
[12702,"Al"]
[8740,"Megan"]
[6283,"Megan"]
[6091,"Michele"]
[3859,"Megan"]
[10279,"Joel"]
[9257,"Michele"]
[9234,"Megan"]
[10256,"Megan"]
[791,"Gwen"]
[7117,"Gwen"]
[1010,"Luong"]
[5969,"Al"]
[11534,"Gwen"]
[4768,"Al"]
[12434,"Michele"]
[8201,"Joel"]
[3932,"Al"]
[915,"Michele"]
[9498,"Al"]
[8578,"Megan"]
[7973,"Joel"]
[3521,"Gwen"]
[2944,"Joel"]
[1875,"Luong"]
[7823,"Joel"]
[2276,"Al"]
[6242,"Luong"]
[6394,"Gwen"]
[1672,"Megan"]
[6699,"Al"]
[12049,"Megan"]
[5057,"Al"]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[{"$f":"IF(MOD(ROW(),10)=0,RANDBETWEEN(7899,12999),IF(MOD(ROW(),2)=0,RANDBETWEEN(1000,6000),RANDBETWEEN(250,10000)))","v":2192}]
[{"$f":"IF(MOD(ROW(),10)=0,RANDBETWEEN(7899,12999),IF(MOD(ROW(),2)=0,RANDBETWEEN(1000,6000),RANDBETWEEN(250,10000)))","v":3343}]
[4675]
[5556]
[9539]
[3728]
[4393]
[986]
[3050]
[2514]
[4864]
[6684]
[5688]
[3694]
[8751]
[1614]
[1465]
[2573]
[3867]
[938]
[4930]
[6329]

{"sheet":"Statistics (rand)","index":12,"n_rows":167,"n_cols":43,"rows_kept":167,"cut":false,"hidden":false,"merged":[]}
["When should you name ranges? When you have data that you will refer to often. If data is in Excel Table format, Table names are very convienient."]
[]
["Why do we need averages? Because we need to have one number that will represent all the numbers in the data set. We need to have a \"typical value\" that will represent all the data points.",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"n =","total # observations",{"$f":"COUNT(Sales)","v":0},"count"]
["Mean = (add them up)/Count = Most common average = AVERAGE = ",null,null,{"$f":"AVERAGE(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"k =","# of classes",6,"type in till TRUE"]
["Median = after ranking, which is in middle (if even number, then add 2 in middle and divide by 2) = good when you don't want very large or small numbers pulling the mean up or down (think of real estate ) = MEDIAN =",null,null,{"$f":"MEDIAN(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,{"$f":"2^AE4>=AE3","v":true},"2^k > = n"]
["Mode = the one that occurs most frequently (not always a mode or sometimes theer can be more than 1 mode) = this average is good when you are counting (think of prefer/notPrefer in a soft drink test - adding all the ones and dividing by the count yields 1) = MODE =",null,null,{"$f":"MODE(Sales)","v":{"$error":"#NAME?"}},{"$f":"COUNTIF(Sales,D6)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Max",{"$f":"MAX(Sales)","v":{"$error":"#NAME?"}}]
["Why do we need Standard Deviation (a measure of variation in data)? Because we need to know if our mean represents that data points fairly!",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Min",{"$f":"MIN(Sales)","v":{"$error":"#NAME?"}}]
["Standard Deviation for a sample = tells you \"how good your mean is\", or \"how fairly the mean represents all the data points, or \"on average, how far away from the average is the actual data point?\", SQRT(SUM((X - Xmean)^2)/(CountOf(X - Xman) - 1)) = STDEV =",null,null,{"$f":"STDEV(Sales)","v":{"$error":"#NAME?"}},{"$f":"SQRT((SUM((Sales-AVERAGE(Sales))^2)/(COUNT(Sales)-1)))","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Range",{"$f":"AE6-AE7","v":{"$error":"#NAME?"}}]
["Mean Deviation = \"how good is your mean\" = SUM(ASB(X - Xmean))/(CountOf(X - Xman) - 1) = AVEDEV =",null,null,{"$f":"AVEDEV(Sales)","v":{"$error":"#NAME?"}},{"$f":"SUM(ABS(Sales-AVERAGE(Sales)))/COUNT(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Class Interval = (Max - Min)/k =",{"$f":"AE8/AE4","v":{"$error":"#NAME?"}}]
["Maximum = what value is the largest = MAX =",null,null,{"$f":"MAX(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Class Interval (always round up) =",{"$f":"CEILING(D12/AE4,500)","v":{"$error":"#NAME?"}}]
["Minimum = what value is the smallest = MAX =",null,null,{"$f":"MIN(Sales)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Lower Limit of first class",0]
["MAX - MIN = Range",null,null,{"$f":"D10-D11","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Upper Limit of last class",13000]
["Count # of Sales using \"numbers\" = COUNT =",null,null,{"$f":"COUNT(Sales)","v":0}]
["Count # of Sales using \"Text\", or non-empty cells = COUNTA =",null,null,{"$f":"COUNTA(SalesReps)","v":1}]
["Skew = 1) 0 = Bell shaped ==> mean = median = mode; 2) -# = curve titled toward right ==> Mean < Median < Mode (mean pulled down by a few small numbers); +# = curve titled toward left Mean > Median > Mode (Mean is pulled up by a few large numbers).",null,null,{"$f":"SKEW(Sales)","v":{"$error":"#NAME?"}}]
[]
["Sales Total Rank Table & Bonus Total",null,null,null,"Bonus Amount",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Rank with ties receiving same value",null,null,null,"Rank with no Ties, 1st and 2nd tie get \"add 1\"",null,null,null,"Rank with no Ties, each tie gets same value"]
["Sales Rep (Category)","Frequency","Rank",50000,2000,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Sales Rep (Category)","Frequency","Rank",null,"Sales Rep (Category)","Frequency","Rank",null,"Sales Rep (Category)","Frequency","Rank"]
["Al",{"$f":"SUMIF($B$59:$B$115,A19,Sales)","v":{"$error":"#NAME?"}},{"$f":"RANK(B19,B$19:B$24,0)","v":{"$error":"#NAME?"}},{"$f":"IF(B19>=D$18,E$18,0)","v":{"$error":"#NAME?"}},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Al",5000,{"$f":"RANK(AH19,AH$19:AH$24,0)+COUNTIF(AH$18:AH18,AH19)","v":2},null,"Al",5000,{"$f":"RANK(AL19,AL$19:AL$24,0)+COUNTIF(AL$18:AL18,AL19)","v":2},null,"Al",5000,{"$f":"RANK(AP19,AP$19:AP$24,0)+(COUNT(AP$19:AP$24)+1-RANK(AP19,AP$19:AP$24,0)-RANK(AP19,AP$19:AP$24,1))/2","v":3}]
["Gwen",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Gwen",5000,{"$f":"RANK(AH20,AH$19:AH$24,0)+COUNTIF(AH$18:AH19,AH20)","v":3},null,"Gwen",5000,{"$f":"RANK(AL20,AL$19:AL$24,0)+COUNTIF(AL$18:AL19,AL20)","v":3},null,"Gwen",5000,3]
["Michele",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Michele",5000,{"$f":"RANK(AH21,AH$19:AH$24,0)+COUNTIF(AH$18:AH20,AH21)","v":4},null,"Michele",5000,{"$f":"RANK(AL21,AL$19:AL$24,0)+COUNTIF(AL$18:AL20,AL21)","v":4},null,"Michele",5000,3]
["Megan",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Megan",5890,{"$f":"RANK(AH22,AH$19:AH$24,0)+COUNTIF(AH$18:AH21,AH22)","v":1},null,"Megan",5890,{"$f":"RANK(AL22,AL$19:AL$24,0)+COUNTIF(AL$18:AL21,AL22)","v":1},null,"Megan",5890,1]
["Luong",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Luong",4900,{"$f":"RANK(AH23,AH$19:AH$24,0)+COUNTIF(AH$18:AH22,AH23)","v":5},null,"Luong",4900,{"$f":"RANK(AL23,AL$19:AL$24,0)+COUNTIF(AL$18:AL22,AL23)","v":5},null,"Luong",4900,5.5]
["Joel",{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Joel",4900,{"$f":"RANK(AH24,AH$19:AH$24,0)+COUNTIF(AH$18:AH23,AH24)","v":6},null,"Joel",4900,{"$f":"RANK(AL24,AL$19:AL$24,0)+COUNTIF(AL$18:AL23,AL24)","v":6},null,"Joel",4900,5.5]
[]
["Number Of Sales Rank Table (Frequency Table)"]
["Sales Rep (Category)","Frequency","Relative Frequency","Rank"]
["Al",{"$f":"COUNTIF($B$59:$B$115,A28)","v":6},{"$f":"B28/B$34","v":0.10526315789473684},{"$f":"RANK(B28,B28:B33,0)","v":6}]
["Gwen",12,0.21052631578947367,3]
["Michele",17,0.2982456140350877,2]
["Megan",7,0.12280701754385964,{"$f":"RANK(B31,B31:B38,0)","v":{"$error":"#NAME?"}}]
["Luong",8,0.14035087719298245,{"$f":"RANK(B32,B32:B39,0)","v":{"$error":"#NAME?"}}]
["Joel",7,0.12280701754385964,{"$f":"RANK(B33,B33:B40,0)","v":{"$error":"#NAME?"}}]
[null,{"$f":"SUM(B28:B33)","v":57}]
[]
["Lower limit of first class","Class interval"]
[0,{"$f":"AE10","v":{"$error":"#NAME?"}}]
["Lower Class Limit","Upper Class Limit","Class","Frequency"]
[{"$f":"A37","v":0},{"$f":"A39+B$37","v":{"$error":"#NAME?"}},{"$f":"DOLLAR(A39,0)&\" up to \"&DOLLAR(B39,0)","v":{"$error":"#NAME?"}},{"$f":"COUNTIF(Sales,\"<\"&B39)-COUNTIF(Sales,\"<\"&A39)","v":{"$error":"#NAME?"}}]
[{"$f":"B39","v":{"$error":"#NAME?"}},{"$f":"A40+B$37","v":{"$error":"#NAME?"}},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$f":"B40","v":{"$error":"#NAME?"}},{"$f":"A41+B$37","v":{"$error":"#NAME?"}},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"},{"$error":"#NAME?"}]
[null,null,null,{"$f":"SUM(D39:D45)=COUNT(Sales)","v":{"$error":"#NAME?"}}]
[]
[]
["Largest Sales =",5,null,null,"Smallest Sales =",5]
["Table with 5 Largest Sales",null,null,null,"Table with 5 Largest Sales"]
["Rank","Amount","Sales Rep",null,"Rank","Amount","Sales Rep"]
[{"$f":"IF(ROW(A1)<=B$49,ROW(A1),\"\")","v":1},{"$f":"IF(A52=\"\",\"\",LARGE(Sales,A52))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A51=\"\",B51=\"\"),\"\",INDEX(SalesReps,MATCH(B52,Sales,0)))","v":{"$error":"#NAME?"}},null,{"$f":"IF(ROW(E1)<=F$49,ROW(E1),\"\")","v":1},{"$f":"IF(E52=\"\",\"\",SMALL(Sales,E52))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A52=\"\",B52=\"\"),\"\",INDEX(SalesReps,MATCH(F52,Sales,0)))","v":{"$error":"#NAME?"}}]
[2,{"$f":"IF(A53=\"\",\"\",LARGE(Sales,A53))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A52=\"\",B52=\"\"),\"\",INDEX(SalesReps,MATCH(B53,Sales,0)))","v":{"$error":"#NAME?"}},null,2,{"$f":"IF(E53=\"\",\"\",SMALL(Sales,E53))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A53=\"\",B53=\"\"),\"\",INDEX(SalesReps,MATCH(F53,Sales,0)))","v":{"$error":"#NAME?"}}]
[3,{"$f":"IF(A54=\"\",\"\",LARGE(Sales,A54))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A53=\"\",B53=\"\"),\"\",INDEX(SalesReps,MATCH(B54,Sales,0)))","v":{"$error":"#NAME?"}},null,3,{"$f":"IF(E54=\"\",\"\",SMALL(Sales,E54))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A54=\"\",B54=\"\"),\"\",INDEX(SalesReps,MATCH(F54,Sales,0)))","v":{"$error":"#NAME?"}}]
[4,{"$f":"IF(A55=\"\",\"\",LARGE(Sales,A55))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A54=\"\",B54=\"\"),\"\",INDEX(SalesReps,MATCH(B55,Sales,0)))","v":{"$error":"#NAME?"}},null,4,{"$f":"IF(E55=\"\",\"\",SMALL(Sales,E55))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A55=\"\",B55=\"\"),\"\",INDEX(SalesReps,MATCH(F55,Sales,0)))","v":{"$error":"#NAME?"}}]
[5,{"$f":"IF(A56=\"\",\"\",LARGE(Sales,A56))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A55=\"\",B55=\"\"),\"\",INDEX(SalesReps,MATCH(B56,Sales,0)))","v":{"$error":"#NAME?"}},null,5,{"$f":"IF(E56=\"\",\"\",SMALL(Sales,E56))","v":{"$error":"#NAME?"}},{"$f":"IF(OR(A56=\"\",B56=\"\"),\"\",INDEX(SalesReps,MATCH(F56,Sales,0)))","v":{"$error":"#NAME?"}}]
[]
["Sales","Sales Rep"]
[{"$f":"RANDBETWEEN(450,12999)","v":5535},{"$f":"CHOOSE(RANDBETWEEN(1,6),\"Joel\",\"Al\",\"Michele\",\"Gwen\",\"Megan\",\"Luong\")","v":"Michele"}]
[{"$f":"RANDBETWEEN(450,12999)","v":8077},"Michele"]
[2387,"Gwen"]
[11548,"Joel"]
[3785,"Gwen"]
[9346,"Michele"]
[546,"Luong"]
[12653,"Gwen"]
[5997,"Megan"]
[8151,"Gwen"]
[834,"Joel"]
[8694,"Megan"]
[4671,"Gwen"]
[7630,"Michele"]
[9372,"Al"]
[1525,"Luong"]
[6258,"Michele"]
[4619,"Michele"]
[4227,"Al"]
[6744,"Gwen"]
[5545,"Joel"]
[8123,"Michele"]
[12839,"Gwen"]
[9576,"Michele"]
[674,"Luong"]
[8540,"Megan"]
[2166,"Gwen"]
[5104,"Megan"]
[10056,"Luong"]
[9496,"Luong"]
[9108,"Megan"]
[6058,"Michele"]
[11287,"Michele"]
[3063,"Joel"]
[8820,"Luong"]
[6212,"Michele"]
[3931,"Al"]
[5634,"Joel"]
[11027,"Megan"]
[5106,"Megan"]
[11742,"Gwen"]
[9316,"Michele"]
[11260,"Michele"]
[8026,"Luong"]
[9704,"Michele"]
[12331,"Al"]
[5610,"Michele"]
[1761,"Gwen"]
[6037,"Gwen"]
[10321,"Michele"]
[517,"Joel"]
[1087,"Al"]
[1444,"Michele"]
[8856,"Luong"]
[5061,"Joel"]
[11836,"Al"]
[12556,"Gwen"]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[{"$f":"IF(MOD(ROW(),10)=0,RANDBETWEEN(7899,12999),IF(MOD(ROW(),2)=0,RANDBETWEEN(1000,6000),RANDBETWEEN(250,10000)))","v":4887}]
[{"$f":"IF(MOD(ROW(),10)=0,RANDBETWEEN(7899,12999),IF(MOD(ROW(),2)=0,RANDBETWEEN(1000,6000),RANDBETWEEN(250,10000)))","v":1861}]
[4484]
[9983]
[11423]
[9427]
[5183]
[2013]
[4609]
[9076]
[3817]
[8933]
[2693]
[1944]
[10457]
[9434]
[4902]
[2432]
[1161]
[442]
[4105]
[1263]

{"sheet":"Normal Curve","index":13,"n_rows":8007,"n_cols":4,"rows_kept":8007,"cut":false,"hidden":false,"merged":[]}
["Mean of Sample = AVERAGE =",5000]
["Standard Deviation of Sample = STDEV =",1000]
[]
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{"sheet":"Line & X Y Scatter Diagram","index":14,"n_rows":21,"n_cols":8,"rows_kept":21,"cut":false,"hidden":false,"merged":[]}
["Years","Number of Customers",null,null,null,null,"Customers Contacted","Total Sales"]
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["1990-01-01",98622,null,null,null,null,938,1368542]
["1991-01-01",80250,null,null,null,null,659,1043856]
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["1999-01-01",433932,null,null,null,null,864,1404864]
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{"sheet":"Line & X Y Scatter Diagram (an)","index":15,"n_rows":21,"n_cols":8,"rows_kept":21,"cut":false,"hidden":false,"merged":[]}
["Years","Number of Customers",null,null,null,null,"Customers Contacted","Total Sales"]
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["1990-01-01",98622,null,null,null,null,938,1368542]
["1991-01-01",80250,null,null,null,null,659,1043856]
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[2006,5069,2682.0105820105823,2386.9894179894177,"Kiko"]
[2007,7225,2890,4335,"Kiko"]
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[2006,15400,6160,9240,"Tatyana"]
[2008,6522,3450.7936507936511,3071.2063492063489,"Victor"]
[2006,15309,6123.6,9185.4,"Kiko"]
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[2009,6802,2720.8,4081.2,"Tatyana"]
[2004,4140,2190.4761904761904,1949.5238095238096,"Tatyana"]
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[2005,2212,1170.3703703703704,1041.6296296296296,"Tatyana"]
[2004,8364,3345.6,5018.3999999999996,"Kiko"]
[2007,6531,3455.5555555555557,3075.4444444444443,"Suix"]
[2004,4769,1907.6,2861.4,"Tatyana"]
[2006,1527,807.93650793650795,719.06349206349205,"Tatyana"]
[2009,8818,3527.2,5290.8,"Wendy"]
[2004,14767,7813.2275132275136,6953.7724867724864,"Suix"]
[2004,5124,2049.6,3074.4,"Wendy"]
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[2004,12715,5086,7629,"Wendy"]
[2004,5222,2762.962962962963,2459.037037037037,"Wendy"]
[2005,5481,2192.4,3288.6,"Wendy"]
[2004,3196,1691.0052910052912,1504.9947089947088,"Wendy"]
[2007,2504,1001.6,1502.4,"Suix"]
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[2009,13143,5257.2,7885.8,"Victor"]
[2005,11236,5944.9735449735454,5291.0264550264546,"Suix"]
[2005,2421,968.4,1452.6,"Kiko"]
[2004,1377,728.57142857142856,648.42857142857144,"Kiko"]
[2008,6264,2505.6,3758.4,"Kiko"]
[2005,8256,4368.2539682539682,3887.7460317460318,"Wendy"]
[2005,14859,5943.6,8915.4,"Suix"]
[2005,9870,5222.2222222222226,4647.7777777777774,"Isaac"]
[2005,3313,1325.2,1987.8,"Isaac"]
[2009,5765,3050.2645502645505,2714.7354497354495,"Wendy"]
[2006,1162,464.8,697.2,"Isaac"]
[2009,6983,3694.7089947089949,3288.2910052910051,"Isaac"]
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[2007,9106,4817.9894179894181,4288.0105820105819,"Tatyana"]
[2004,1373,549.20000000000005,823.8,"Kiko"]
[2006,3867,2046.031746031746,1820.968253968254,"Isaac"]
[2008,1776,710.4,1065.5999999999999,"Tatyana"]
[2005,3407,1802.6455026455028,1604.3544973544972,"Wendy"]
[2008,13287,5314.8,7972.2,"Tatyana"]
[2004,8473,4483.068783068783,3989.931216931217,"Victor"]
[2009,1986,794.4,1191.5999999999999,"Kiko"]
[2005,10688,5655.0264550264556,5032.9735449735444,"Wendy"]
[2006,1884,753.6,1130.4000000000001,"Isaac"]
[2005,6645,3515.8730158730159,3129.1269841269841,"Tatyana"]
[2008,5968,2387.1999999999998,3580.8,"Victor"]
[2004,1942,1027.5132275132275,914.48677248677245,"Victor"]
[2006,15014,6005.6,9008.4,"Victor"]
[2005,7027,3717.9894179894181,3309.0105820105819,"Suix"]
[2006,6247,2498.8000000000002,3748.2,"Kiko"]
[2005,4192,2217.9894179894181,1974.0105820105819,"Tatyana"]
[2005,16129,6451.6,9677.4,"Victor"]
[2006,2537,1342.3280423280423,1194.6719576719577,"Victor"]
[2004,6335,2534,3801,"Isaac"]
[2004,3998,2115.3439153439153,1882.6560846560847,"Isaac"]
[2004,7569,3027.6,4541.3999999999996,"Isaac"]
[2008,2742,1450.7936507936508,1291.2063492063492,"Kiko"]
[2006,6034,2413.6,3620.4,"Victor"]
[2009,5756,3045.5026455026455,2710.4973544973545,"Suix"]
[2004,11280,4512,6768,"Tatyana"]
[2005,15610,8259.2592592592591,7350.7407407407409,"Isaac"]
[2007,7226,2890.4,4335.6000000000004,"Wendy"]
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[2004,15425,6170,9255,"Kiko"]
[2009,15010,7941.798941798942,7068.201058201058,"Kiko"]
[2009,12373,4949.2,7423.8,"Isaac"]
[2007,13230,7000,6230,"Tatyana"]
[2009,4355,1742,2613,"Victor"]
[2007,5936,3140.7407407407409,2795.2592592592591,"Isaac"]
[2009,6035,2414,3621,"Victor"]
[2008,1466,775.6613756613757,690.3386243386243,"Isaac"]
[2006,9592,3836.8,5755.2,"Victor"]
[2008,5328,2819.0476190476193,2508.9523809523807,"Tatyana"]
[2009,3650,1460,2190,"Victor"]
[2008,4094,2166.1375661375664,1927.8624338624336,"Suix"]
[2009,16616,6646.4,9969.6,"Suix"]
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[2007,15193,6077.2,9115.7999999999993,"Tatyana"]
[2004,3771,1995.2380952380954,1775.7619047619046,"Victor"]
[2005,1367,546.79999999999995,820.2,"Tatyana"]
[2009,14480,7661.3756613756614,6818.6243386243386,"Isaac"]
[2008,2888,1155.2,1732.8,"Isaac"]
[2006,14328,7580.9523809523816,6747.0476190476184,"Isaac"]
[2009,6654,2661.6,3992.4,"Suix"]
[2004,4593,2430.1587301587301,2162.8412698412699,"Victor"]
[2004,4558,1823.2,2734.8,"Kiko"]
[2008,11657,6167.7248677248681,5489.2751322751319,"Wendy"]
[2007,10675,4270,6405,"Tatyana"]
[2006,15596,8251.8518518518522,7344.1481481481478,"Wendy"]
[2006,5689,2275.6,3413.4,"Kiko"]
[2005,7921,4191.0052910052909,3729.9947089947091,"Suix"]
[2005,4139,1655.6,2483.4,"Isaac"]
[2007,14266,7548.1481481481487,6717.8518518518513,"Kiko"]
[2009,2059,823.6,1235.4000000000001,"Victor"]
[2004,5060,2677.2486772486773,2382.7513227513227,"Kiko"]
[2008,1213,485.2,727.8,"Kiko"]
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[2006,6450,2580,3870,"Tatyana"]
[2005,10596,5606.3492063492067,4989.6507936507933,"Wendy"]
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[2006,8177,4326.4550264550271,3850.5449735449729,"Tatyana"]
[2004,4014,1605.6,2408.4,"Wendy"]
[2006,2250,1190.4761904761906,1059.5238095238094,"Kiko"]
[2007,15476,6190.4,9285.6,"Isaac"]
[2007,10166,5378.8359788359794,4787.1640211640206,"Isaac"]
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[2009,5557,2940.2116402116403,2616.7883597883597,"Isaac"]
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[2005,5647,2987.830687830688,2659.169312169312,"Tatyana"]
[2007,3436,1374.4,2061.6,"Isaac"]
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[2004,6686,2674.4,4011.6,"Tatyana"]
[2007,3713,1964.5502645502647,1748.4497354497353,"Suix"]
[2008,11878,4751.2,7126.8,"Tatyana"]
[2008,11601,6138.0952380952385,5462.9047619047615,"Victor"]
[2008,3700,1480,2220,"Wendy"]
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[2009,1976,1045.5026455026455,930.49735449735454,"Tatyana"]
[2004,5785,2314,3471,"Victor"]
[2007,5491,2905.2910052910056,2585.7089947089944,"Isaac"]
[2006,6138,2455.1999999999998,3682.8,"Victor"]
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[2006,8117,3246.8,4870.2,"Tatyana"]
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[2004,2477,990.8,1486.2,"Wendy"]
[2004,4244,2245.5026455026455,1998.4973544973545,"Wendy"]
[2005,12998,5199.2,7798.8,"Suix"]
[2005,3654,1933.3333333333335,1720.6666666666665,"Kiko"]
[2008,3214,1285.5999999999999,1928.4,"Suix"]
[2008,974,515.34391534391534,458.65608465608466,"Tatyana"]
[2007,5982,2392.8000000000002,3589.2,"Suix"]
[2008,4663,2467.1957671957675,2195.8042328042325,"Victor"]

{"sheet":"AI,SIS,CIS (an)","index":17,"n_rows":311,"n_cols":14,"rows_kept":311,"cut":false,"hidden":false,"merged":[]}
["Year","Sales","COGS","Profit","SalesRep",null,"Sales Summary"]
[2006,2095,838,1257,"Isaac",null,"Year/SalesRep","Isaac","Kiko","Suix","Tatyana","Victor","Wendy"]
[2006,4022,2128.0423280423283,1893.9576719576717,"Tatyana",null,2004,{"$f":"SUMIFS($B$2:$B$311,$A$2:$A$311,$G3,$E$2:$E$311,H$2\n)","v":70055},105731,17046,54348,40607,72729]
[2006,5542,2216.8000000000002,3325.2,"Suix",null,2005,73122,46329,98219,74928,44534,78019]
[2007,6527,3453.4391534391534,3073.5608465608466,"Kiko",null,2006,97462,65950,38067,70565,93763,88601]
[2005,9392,3756.8,5635.2,"Victor",null,2007,81740,98155,52482,74842,43548,52930]
[2004,16685,8828.0423280423292,7856.9576719576708,"Isaac",null,2008,51587,43031,36211,56967,46002,53897]
[2004,6054,2421.6,3632.4,"Kiko",null,2009,73480,87083,76626,74728,40567,46815]
[2006,6815,3605.8201058201062,3209.1798941798938,"Victor"]
[2006,14894,5957.6,8936.4,"Wendy",null,"Average by Year"]
[2008,16962,8974.6031746031749,7987.3968253968251,"Suix",null,"Year",{"$f":"\"Average \"&B1","v":"Average Sales"},{"$f":"\"Average \"&C1","v":"Average COGS"},{"$f":"\"Average \"&D1","v":"Average Profit"}]
[2006,5160,2064,3096,"Wendy",null,2004,{"$f":"AVERAGEIF($A$2:$A$311,$G12,B$2:B$311)","v":7357.4693877551017},3349.6939423388408,4007.7754454162609]
[2009,8589,4544.4444444444443,4044.5555555555557,"Isaac",null,2005,7833.0377358490568,3735.8052111410616,4097.2325247079962]
[2008,5754,2301.6,3452.4,"Suix",null,2006,7573.4666666666662,3405.8050793650782,4167.661587301588]
[2006,813,430.15873015873018,382.84126984126982,"Tatyana",null,2007,8238.7142857142862,3792.791491199654,4445.9227945146313]
[2007,16027,6410.8,9616.2000000000007,"Kiko",null,2008,6121.1702127659573,2902.3910390633805,3218.7791737025768]
[2006,6874,3637.0370370370374,3236.9629629629626,"Kiko",null,2009,7678.8269230769229,3553.837932437933,4124.9889906389899]
[2005,10545,4218,6327,"Kiko"]
[2006,4027,2130.6878306878307,1896.3121693121693,"Wendy"]
[2009,934,373.6,560.4,"Isaac"]
[2007,16326,8638.0952380952385,7687.9047619047615,"Wendy",null,null,"Values"]
[2009,5968,2387.1999999999998,3580.8,"Kiko",null,"Row Labels","Average of Sales","Average of COGS","Average of Profit"]
[2006,3840,2031.7460317460318,1808.2539682539682,"Victor",null,2004,7357.4693877551017,3349.6939423388408,4007.7754454162609]
[2007,4484,1793.6,2690.4,"Victor",null,2005,7833.0377358490568,3735.8052111410616,4097.2325247079962]
[2006,6317,3342.3280423280426,2974.6719576719574,"Victor",null,2006,7573.4666666666662,3405.8050793650782,4167.661587301588]
[2005,10785,4314,6471,"Kiko",null,2007,8238.7142857142862,3792.791491199654,4445.9227945146313]
[2004,1961,1037.5661375661375,923.43386243386249,"Tatyana",null,2008,6121.1702127659573,2902.3910390633805,3218.7791737025768]
[2005,9765,3906,5859,"Tatyana",null,2009,7678.8269230769229,3553.837932437933,4124.9889906389899]
[2005,11304,5980.9523809523816,5323.0476190476184,"Suix",null,"Grand Total",7486.3419354838707,3463.0313500597358,4023.3105854241335]
[2006,11826,4730.3999999999996,7095.6,"Kiko"]
[2008,2784,1473.015873015873,1310.984126984127,"Isaac"]
[2005,2322,928.8,1393.2,"Suix"]
[2009,5124,2711.1111111111113,2412.8888888888887,"Wendy",null,"Sum of Sales","Column Labels"]
[2008,6472,2588.8000000000002,3883.2,"Isaac",null,"Row Labels","Isaac","Kiko","Suix","Tatyana","Victor","Wendy","Grand Total"]
[2004,4670,2470.899470899471,2199.100529100529,"Tatyana",null,2004,70055,105731,17046,54348,40607,72729,360516]
[2006,7787,3114.8,4672.2,"Tatyana",null,2005,73122,46329,98219,74928,44534,78019,415151]
[2008,10352,5477.2486772486773,4874.7513227513227,"Tatyana",null,2006,97462,65950,38067,70565,93763,88601,454408]
[2009,6085,2434,3651,"Suix",null,2007,81740,98155,52482,74842,43548,52930,403697]
[2008,6432,3403.1746031746034,3028.8253968253966,"Isaac",null,2008,51587,43031,36211,56967,46002,53897,287695]
[2008,5003,2001.2,3001.8,"Wendy",null,2009,73480,87083,76626,74728,40567,46815,399299]
[2009,1372,725.92592592592598,646.07407407407402,"Kiko",null,"Grand Total",447446,446279,318651,406378,309021,392991,2320766]
[2007,3013,1205.2,1807.8,"Isaac"]
[2006,11817,6252.3809523809523,5564.6190476190477,"Victor"]
[2007,6450,2580,3870,"Wendy"]
[2008,10874,5753.4391534391534,5120.5608465608466,"Kiko"]
[2006,4778,1911.2,2866.8,"Wendy"]
[2009,4312,2281.4814814814818,2030.5185185185182,"Victor"]
[2009,15358,6143.2,9214.7999999999993,"Kiko"]
[2008,4352,2302.6455026455028,2049.3544973544972,"Kiko"]
[2004,15905,6362,9543,"Kiko"]
[2005,10283,5440.7407407407409,4842.2592592592591,"Isaac"]
[2005,16052,6420.8,9631.2000000000007,"Victor"]
[2005,5945,3145.5026455026455,2799.4973544973545,"Isaac"]
[2007,5220,2088,3132,"Isaac"]
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[2007,6229,2491.6,3737.4,"Kiko"]
[2004,6563,3472.4867724867727,3090.5132275132273,"Kiko"]
[2008,4692,1876.8,2815.2,"Tatyana"]
[2008,983,520.10582010582016,462.89417989417984,"Suix"]
[2006,10220,4088,6132,"Wendy"]
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[2009,13088,5235.2,7852.8,"Tatyana"]
[2009,5816,3077.2486772486773,2738.7513227513227,"Victor"]
[2006,7475,2990,4485,"Kiko"]
[2009,10348,5475.132275132275,4872.867724867725,"Wendy"]
[2009,862,344.8,517.20000000000005,"Suix"]
[2005,14861,7862.9629629629635,6998.0370370370365,"Kiko"]
[2008,6752,2700.8,4051.2,"Victor"]
[2007,11193,5922.2222222222226,5270.7777777777774,"Tatyana"]
[2006,2428,971.2,1456.8,"Tatyana"]
[2008,11122,5884.6560846560851,5237.3439153439149,"Isaac"]
[2007,2624,1049.5999999999999,1574.4,"Victor"]
[2004,5000,2645.5026455026455,2354.4973544973545,"Wendy"]
[2005,12504,5001.6000000000004,7502.4,"Tatyana"]
[2009,7882,4170.3703703703704,3711.6296296296296,"Isaac"]
[2007,11473,4589.2,6883.8,"Kiko"]
[2008,926,489.94708994708998,436.05291005291002,"Victor"]
[2006,16346,6538.4,9807.6,"Wendy"]
[2007,11773,6229.1005291005295,5543.8994708994705,"Wendy"]
[2009,16760,6704,10056,"Wendy"]
[2004,866,458.20105820105823,407.79894179894177,"Suix"]
[2009,13599,5439.6,8159.4,"Kiko"]
[2009,13724,7261.3756613756614,6462.6243386243386,"Tatyana"]
[2009,2245,898,1347,"Tatyana"]
[2008,3233,1710.5820105820108,1522.4179894179892,"Wendy"]
[2004,1413,565.20000000000005,847.8,"Suix"]
[2008,5323,2816.4021164021165,2506.5978835978835,"Tatyana"]
[2005,1927,770.8,1156.2,"Tatyana"]
[2009,4432,2344.9735449735449,2087.0264550264551,"Tatyana"]
[2006,6437,2574.8000000000002,3862.2,"Tatyana"]
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[2006,13446,5378.4,8067.6,"Victor"]
[2006,10343,5472.4867724867727,4870.5132275132273,"Suix"]
[2007,905,362,543,"Wendy"]
[2008,11016,5828.5714285714284,5187.4285714285716,"Kiko"]
[2009,11238,4495.2,6742.8,"Tatyana"]
[2005,9512,5032.8042328042329,4479.1957671957671,"Isaac"]
[2007,10250,4100,6150,"Wendy"]
[2005,5149,2724.3386243386244,2424.6613756613756,"Tatyana"]
[2007,1141,456.4,684.6,"Isaac"]
[2005,6788,3591.5343915343919,3196.4656084656081,"Tatyana"]
[2008,1970,788,1182,"Tatyana"]
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[2006,6861,2744.4,4116.6000000000004,"Suix"]
[2005,12837,6792.063492063492,6044.936507936508,"Wendy"]
[2009,16760,6704,10056,"Suix"]
[2007,13032,6895.2380952380954,6136.7619047619046,"Victor"]
[2008,7271,2908.4,4362.6000000000004,"Isaac"]
[2006,5211,2757.1428571428573,2453.8571428571427,"Kiko"]
[2004,6847,2738.8,4108.2,"Isaac"]
[2006,3219,1703.1746031746034,1515.8253968253966,"Wendy"]
[2008,6570,2628,3942,"Kiko"]
[2005,15941,8434.3915343915342,7506.6084656084658,"Suix"]
[2005,2961,1184.4000000000001,1776.6,"Victor"]
[2007,14127,7474.6031746031749,6652.3968253968251,"Isaac"]
[2006,16013,6405.2,9607.7999999999993,"Isaac"]
[2005,4308,2279.3650793650795,2028.6349206349205,"Tatyana"]
[2009,5754,2301.6,3452.4,"Tatyana"]
[2008,3858,2041.2698412698414,1816.7301587301586,"Wendy"]
[2005,6411,2564.4,3846.6,"Isaac"]
[2005,14424,7631.7460317460318,6792.2539682539682,"Tatyana"]
[2009,1197,478.8,718.2,"Victor"]
[2006,3015,1595.2380952380954,1419.7619047619046,"Isaac"]
[2008,11608,4643.2,6964.8,"Isaac"]
[2009,5612,2969.3121693121693,2642.6878306878307,"Tatyana"]
[2007,16534,6613.6,9920.4,"Kiko"]
[2009,9857,5215.3439153439158,4641.6560846560842,"Tatyana"]
[2004,6641,2656.4,3984.6,"Kiko"]
[2006,14361,7598.4126984126988,6762.5873015873012,"Wendy"]
[2004,13806,5522.4,8283.6,"Isaac"]
[2007,2717,1437.5661375661377,1279.4338624338623,"Isaac"]
[2007,15064,6025.6,9038.4,"Suix"]
[2006,4094,2166.1375661375664,1927.8624338624336,"Isaac"]
[2006,2842,1136.8,1705.2,"Tatyana"]
[2006,6244,3303.7037037037039,2940.2962962962961,"Isaac"]
[2007,10514,4205.6000000000004,6308.4,"Suix"]
[2009,5769,3052.3809523809527,2716.6190476190473,"Kiko"]
[2006,15321,6128.4,9192.6,"Suix"]
[2005,7338,3882.5396825396829,3455.4603174603171,"Wendy"]
[2007,14592,5836.8,8755.2000000000007,"Kiko"]
[2004,5795,3066.1375661375664,2728.8624338624336,"Kiko"]
[2005,8039,3215.6,4823.3999999999996,"Isaac"]
[2008,13458,7120.6349206349214,6337.3650793650786,"Wendy"]
[2009,5844,2337.6,3506.4,"Kiko"]
[2008,915,484.12698412698415,430.87301587301585,"Wendy"]
[2007,6447,2578.8000000000002,3868.2,"Tatyana"]
[2009,1936,1024.3386243386244,911.66137566137559,"Isaac"]
[2006,12213,4885.2,7327.8,"Victor"]
[2007,1352,715.34391534391534,636.65608465608466,"Victor"]
[2009,6849,2739.6,4109.3999999999996,"Suix"]
[2005,15193,8038.6243386243386,7154.3756613756614,"Wendy"]
[2006,4780,1912,2868,"Isaac"]
[2007,5609,2967.7248677248681,2641.2751322751319,"Suix"]
[2005,2622,1048.8,1573.2,"Wendy"]
[2004,3964,2097.3544973544977,1866.6455026455023,"Tatyana"]
[2007,2888,1155.2,1732.8,"Isaac"]
[2004,16878,8930.1587301587315,7947.8412698412685,"Tatyana"]
[2004,11891,4756.3999999999996,7134.6,"Wendy"]
[2007,8998,4760.8465608465613,4237.1534391534387,"Tatyana"]
[2004,12017,4806.8,7210.2,"Kiko"]
[2004,1914,1012.6984126984128,901.30158730158723,"Isaac"]
[2008,5204,2081.6,3122.4,"Suix"]
[2009,16362,8657.1428571428569,7704.8571428571431,"Kiko"]
[2008,9570,3828,5742,"Victor"]
[2005,3069,1623.8095238095239,1445.1904761904761,"Kiko"]
[2007,5526,2210.4,3315.6,"Isaac"]
[2006,1288,681.48148148148152,606.51851851851848,"Isaac"]
[2007,5282,2112.8000000000002,3169.2,"Kiko"]
[2006,5069,2682.0105820105823,2386.9894179894177,"Kiko"]
[2007,7225,2890,4335,"Kiko"]
[2009,14746,7802.1164021164022,6943.8835978835978,"Isaac"]
[2006,15400,6160,9240,"Tatyana"]
[2008,6522,3450.7936507936511,3071.2063492063489,"Victor"]
[2006,15309,6123.6,9185.4,"Kiko"]
[2006,6565,3473.5449735449738,3091.4550264550262,"Tatyana"]
[2009,6802,2720.8,4081.2,"Tatyana"]
[2004,4140,2190.4761904761904,1949.5238095238096,"Tatyana"]
[2005,994,397.6,596.4,"Kiko"]
[2005,1601,847.08994708994715,753.91005291005285,"Wendy"]
[2005,3311,1324.4,1986.6,"Suix"]
[2005,2212,1170.3703703703704,1041.6296296296296,"Tatyana"]
[2004,8364,3345.6,5018.3999999999996,"Kiko"]
[2007,6531,3455.5555555555557,3075.4444444444443,"Suix"]
[2004,4769,1907.6,2861.4,"Tatyana"]
[2006,1527,807.93650793650795,719.06349206349205,"Tatyana"]
[2009,8818,3527.2,5290.8,"Wendy"]
[2004,14767,7813.2275132275136,6953.7724867724864,"Suix"]
[2004,5124,2049.6,3074.4,"Wendy"]
[2006,4190,2216.931216931217,1973.068783068783,"Isaac"]
[2005,9431,3772.4,5658.6,"Suix"]
[2008,12073,6387.8306878306885,5685.1693121693115,"Wendy"]
[2004,12715,5086,7629,"Wendy"]
[2004,5222,2762.962962962963,2459.037037037037,"Wendy"]
[2005,5481,2192.4,3288.6,"Wendy"]
[2004,3196,1691.0052910052912,1504.9947089947088,"Wendy"]
[2007,2504,1001.6,1502.4,"Suix"]
[2009,5060,2677.2486772486773,2382.7513227513227,"Kiko"]
[2009,13143,5257.2,7885.8,"Victor"]
[2005,11236,5944.9735449735454,5291.0264550264546,"Suix"]
[2005,2421,968.4,1452.6,"Kiko"]
[2004,1377,728.57142857142856,648.42857142857144,"Kiko"]
[2008,6264,2505.6,3758.4,"Kiko"]
[2005,8256,4368.2539682539682,3887.7460317460318,"Wendy"]
[2005,14859,5943.6,8915.4,"Suix"]
[2005,9870,5222.2222222222226,4647.7777777777774,"Isaac"]
[2005,3313,1325.2,1987.8,"Isaac"]
[2009,5765,3050.2645502645505,2714.7354497354495,"Wendy"]
[2006,1162,464.8,697.2,"Isaac"]
[2009,6983,3694.7089947089949,3288.2910052910051,"Isaac"]
[2004,16043,6417.2,9625.7999999999993,"Victor"]
[2007,9106,4817.9894179894181,4288.0105820105819,"Tatyana"]
[2004,1373,549.20000000000005,823.8,"Kiko"]
[2006,3867,2046.031746031746,1820.968253968254,"Isaac"]
[2008,1776,710.4,1065.5999999999999,"Tatyana"]
[2005,3407,1802.6455026455028,1604.3544973544972,"Wendy"]
[2008,13287,5314.8,7972.2,"Tatyana"]
[2004,8473,4483.068783068783,3989.931216931217,"Victor"]
[2009,1986,794.4,1191.5999999999999,"Kiko"]
[2005,10688,5655.0264550264556,5032.9735449735444,"Wendy"]
[2006,1884,753.6,1130.4000000000001,"Isaac"]
[2005,6645,3515.8730158730159,3129.1269841269841,"Tatyana"]
[2008,5968,2387.1999999999998,3580.8,"Victor"]
[2004,1942,1027.5132275132275,914.48677248677245,"Victor"]
[2006,15014,6005.6,9008.4,"Victor"]
[2005,7027,3717.9894179894181,3309.0105820105819,"Suix"]
[2006,6247,2498.8000000000002,3748.2,"Kiko"]
[2005,4192,2217.9894179894181,1974.0105820105819,"Tatyana"]
[2005,16129,6451.6,9677.4,"Victor"]
[2006,2537,1342.3280423280423,1194.6719576719577,"Victor"]
[2004,6335,2534,3801,"Isaac"]
[2004,3998,2115.3439153439153,1882.6560846560847,"Isaac"]
[2004,7569,3027.6,4541.3999999999996,"Isaac"]
[2008,2742,1450.7936507936508,1291.2063492063492,"Kiko"]
[2006,6034,2413.6,3620.4,"Victor"]
[2009,5756,3045.5026455026455,2710.4973544973545,"Suix"]
[2004,11280,4512,6768,"Tatyana"]
[2005,15610,8259.2592592592591,7350.7407407407409,"Isaac"]
[2007,7226,2890.4,4335.6000000000004,"Wendy"]
[2007,6387,3379.3650793650795,3007.6349206349205,"Victor"]
[2004,15425,6170,9255,"Kiko"]
[2009,15010,7941.798941798942,7068.201058201058,"Kiko"]
[2009,12373,4949.2,7423.8,"Isaac"]
[2007,13230,7000,6230,"Tatyana"]
[2009,4355,1742,2613,"Victor"]
[2007,5936,3140.7407407407409,2795.2592592592591,"Isaac"]
[2009,6035,2414,3621,"Victor"]
[2008,1466,775.6613756613757,690.3386243386243,"Isaac"]
[2006,9592,3836.8,5755.2,"Victor"]
[2008,5328,2819.0476190476193,2508.9523809523807,"Tatyana"]
[2009,3650,1460,2190,"Victor"]
[2008,4094,2166.1375661375664,1927.8624338624336,"Suix"]
[2009,16616,6646.4,9969.6,"Suix"]
[2008,1544,816.93121693121702,727.06878306878298,"Isaac"]
[2007,15193,6077.2,9115.7999999999993,"Tatyana"]
[2004,3771,1995.2380952380954,1775.7619047619046,"Victor"]
[2005,1367,546.79999999999995,820.2,"Tatyana"]
[2009,14480,7661.3756613756614,6818.6243386243386,"Isaac"]
[2008,2888,1155.2,1732.8,"Isaac"]
[2006,14328,7580.9523809523816,6747.0476190476184,"Isaac"]
[2009,6654,2661.6,3992.4,"Suix"]
[2004,4593,2430.1587301587301,2162.8412698412699,"Victor"]
[2004,4558,1823.2,2734.8,"Kiko"]
[2008,11657,6167.7248677248681,5489.2751322751319,"Wendy"]
[2007,10675,4270,6405,"Tatyana"]
[2006,15596,8251.8518518518522,7344.1481481481478,"Wendy"]
[2006,5689,2275.6,3413.4,"Kiko"]
[2005,7921,4191.0052910052909,3729.9947089947091,"Suix"]
[2005,4139,1655.6,2483.4,"Isaac"]
[2007,14266,7548.1481481481487,6717.8518518518513,"Kiko"]
[2009,2059,823.6,1235.4000000000001,"Victor"]
[2004,5060,2677.2486772486773,2382.7513227513227,"Kiko"]
[2008,1213,485.2,727.8,"Kiko"]
[2009,5327,2818.5185185185187,2508.4814814814813,"Suix"]
[2006,6450,2580,3870,"Tatyana"]
[2005,10596,5606.3492063492067,4989.6507936507933,"Wendy"]
[2006,15966,6386.4,9579.6,"Isaac"]
[2006,8177,4326.4550264550271,3850.5449735449729,"Tatyana"]
[2004,4014,1605.6,2408.4,"Wendy"]
[2006,2250,1190.4761904761906,1059.5238095238094,"Kiko"]
[2007,15476,6190.4,9285.6,"Isaac"]
[2007,10166,5378.8359788359794,4787.1640211640206,"Isaac"]
[2004,2461,984.4,1476.6,"Wendy"]
[2009,5557,2940.2116402116403,2616.7883597883597,"Isaac"]
[2008,1387,554.79999999999995,832.2,"Tatyana"]
[2005,5647,2987.830687830688,2659.169312169312,"Tatyana"]
[2007,3436,1374.4,2061.6,"Isaac"]
[2009,11717,6199.4708994708999,5517.5291005291001,"Suix"]
[2004,6686,2674.4,4011.6,"Tatyana"]
[2007,3713,1964.5502645502647,1748.4497354497353,"Suix"]
[2008,11878,4751.2,7126.8,"Tatyana"]
[2008,11601,6138.0952380952385,5462.9047619047615,"Victor"]
[2008,3700,1480,2220,"Wendy"]
[2007,6603,3493.6507936507937,3109.3492063492063,"Isaac"]
[2004,16599,6639.6,9959.4,"Kiko"]
[2009,1976,1045.5026455026455,930.49735449735454,"Tatyana"]
[2004,5785,2314,3471,"Victor"]
[2007,5491,2905.2910052910056,2585.7089947089944,"Isaac"]
[2006,6138,2455.1999999999998,3682.8,"Victor"]
[2004,12901,6825.9259259259261,6075.0740740740739,"Isaac"]
[2006,8117,3246.8,4870.2,"Tatyana"]
[2009,755,399.4708994708995,355.5291005291005,"Kiko"]
[2007,2565,1026,1539,"Suix"]
[2004,16385,8669.3121693121702,7715.6878306878298,"Wendy"]
[2004,2477,990.8,1486.2,"Wendy"]
[2004,4244,2245.5026455026455,1998.4973544973545,"Wendy"]
[2005,12998,5199.2,7798.8,"Suix"]
[2005,3654,1933.3333333333335,1720.6666666666665,"Kiko"]
[2008,3214,1285.5999999999999,1928.4,"Suix"]
[2008,974,515.34391534391534,458.65608465608466,"Tatyana"]
[2007,5982,2392.8000000000002,3589.2,"Suix"]
[2008,4663,2467.1957671957675,2195.8042328042325,"Victor"]

{"sheet":"Simulation","index":18,"n_rows":7,"n_cols":5,"rows_kept":7,"cut":false,"hidden":false,"merged":[]}
["Next Yer Projected Sales"]
["Products","Price Low","Price High","Units Sold Low","Units Sold High"]
["Boomerang 01",{"$f":"ROUND(15+RAND()*0.5,2)","v":15.19},{"$f":"B3+ROUND(RAND()*1,2)","v":15.85}]
["Boomerang 02",{"$f":"ROUND(18+RAND()*0.5,2)","v":18.010000000000002},18.59]
["Boomerang 03",{"$f":"ROUND(20+RAND()*0.5,2)","v":20.28},20.52]
["Boomerang 04",{"$f":"ROUND(25+RAND()*0.5,2)","v":25.48},26.29]
["Boomerang 05",{"$f":"ROUND(23+RAND()*1,2)","v":23.79},24.22]

{"sheet":"Chart Elements Types","index":19,"n_rows":40,"n_cols":3,"rows_kept":40,"cut":false,"hidden":false,"merged":[]}
["Chart Elements"]
[{"$f":"ROWS($B$2:B2)","v":1},"Chart title","The descriptive text that identifies the chart's contents"]
[{"$f":"ROWS($B$2:B3)","v":2},"Y-axis","The vertical axis where data values are plotted"]
[{"$f":"ROWS($B$2:B4)","v":3},"Y-axis labels","The labels that identify the data values plotted on the Y-axis"]
[{"$f":"ROWS($B$2:B5)","v":4},"X-axis","The horizontal axis where categories are plotted"]
[{"$f":"ROWS($B$2:B6)","v":5},"X-axis labels","The labels that identify the categories plotted on the X-axis"]
[{"$f":"ROWS($B$2:B7)","v":6},"Data Series","The related data points that are plotted on the chart; each data series on a chart has a unique color or pattern and is identified in the chart legend"]
[{"$f":"ROWS($B$2:B8)","v":7},"Data Points","The points in a data series at which the X-axis and Y-axis values intersect"]
[{"$f":"ROWS($B$2:B9)","v":8},"Legend","A box that identifies the patterns or colors assigned to the data series in a chart"]
[{"$f":"ROWS($B$2:B10)","v":9},"Category","This is the term that Excel uses to describe labels"]
[{"$f":"ROWS($B$2:B11)","v":10},"Secondary Y-axis","Common way to include widely differing sets of data from the same time period."]
[]
["Chart Types"]
[{"$f":"ROWS($B$14:B14)","v":1},"Column (or Cylinder, or Cone, or Pyramid)","Compares values across categories in a vertical orientation. Values are indicated by the height of the columns. Compare means the difference between the different numeric data points. If you are comparing, use a column or bar instead of a line chart."]
[{"$f":"ROWS($B$14:B15)","v":2},"Stacked Column Vertical axis in %","Compares the % of each value to the sum of the values for a given category and the overall column represent the 100%. Stacked charts do a good job illustrating the cumulative effects of data in categories. These charts can reduce confusion about whether the line on the chart represents individual values or cumulative contribution to the whole. These cahrts nicely combine pie, area, column, and line elements."]
[{"$f":"ROWS($B$14:B16)","v":3},"Stacked Column Vertical axis in amount","Compares the amount of each value for each category and the overall column represent the sum of the all the values for the category. (Stacked charts do a good job illustrating the cumulative effects of data in categories)"]
[{"$f":"ROWS($B$14:B17)","v":4},"Bar","Compares values across categories in a horizontal orientation. Values are indicated by the length of the bars (good for emphasizing differences)."]
[{"$f":"ROWS($B$14:B18)","v":5},"Line","Displays trends over time or by category. Values are indicated by the highest of the lines. Trends means up, down, flat. If it is trends you want, use line, not column. A line chart plots numeric values on one axis and category labels equidistantly on the other axis, (whereas the XY (Scatter) chart plots numeric values on both the X- and Y-axes based on the value of the data )."]
[{"$f":"ROWS($B$14:B19)","v":6},"Stacked Line","Same as \"Stacked Area, Values\" except it is just lines"]
[{"$f":"ROWS($B$14:B20)","v":7},"XY (Scatter)","Compares pairs of numeric values on the X- and Y-axes; can also be used to display a functional relationship, such as y = mx + b. Values are indicated by the position of the data points. XY (Scatter) will provide a buffer on each end (a little less at the beginning and a little more at the end. The XY (Scatter) chart plots numeric values on both the X- and Y-axes based on the value of the data (whereas a line chart plots numeric values on one axis and category labels equidistantly on the other axis). An XY (Scatter) should be used instead of a line chart when comparing sets of numerical data on both the X-axis and the Y-axis."]
[{"$f":"ROWS($B$14:B21)","v":8},"Area","Displays trends over time or by category. Values are indicated by the filled area below the lines. This chart is a combination of line chart and column chart in that it fills below the line (like a column) and shows a trend over time or category."]
[{"$f":"ROWS($B$14:B22)","v":9},"Stacked Area, Values","Sales example: Illustrates sales trends while still emphasizing the contribution that each category made to a particular year's performance (vertical axis is the sum of the 4 for the year!)  Be careful with Stacked Area charts with multiple data series because \"These charts can give the impression that each line represents the actual values in the data series\"."]
[{"$f":"ROWS($B$14:B23)","v":10},"Stacked Area, 100%"]
[{"$f":"ROWS($B$14:B24)","v":11},"Pie","Compares the contribution each value in a single numeric data series makes to the whole, or 100%. Values are indicated by the size of the pie slices. Use this chart to show the relative percentages rather than values - graphing these percentages can allow a viewer to make quick visual comparisons."]
[{"$f":"ROWS($B$14:B25)","v":12},"Pie of Pie","When you have too many segments. The key is that after you crate it, right-click the pie and point to Format Data Series, Options Tab, adjust the number of items you want in the pie of pie (smallest - must have data in sheet sorted descending). You can use one of four methods to do this: Position, Value, %, Custom (drag and drop pie pieces)"]
[{"$f":"ROWS($B$14:B26)","v":13},"Doughnut","Compares the contribution each value in multiple numeric data series make to the whole, or 100%. Values are indicated by the size of the doughnut segments. Advantage over \"Stacked Column, 100%\" is that they can show the individual % for each individual segment. Disatvantage of Doughnut is that they quickly get too busy."]
[{"$f":"ROWS($B$14:B27)","v":14},"Stock","Displays stock price and volume trends over time. Plotted values can include volume, opening price, highest price, lowest price, and closing price. Vetical line represents High and Low; dash represnts close. Read chart sub-type for an indication of how to place data in sheet."]
[{"$f":"ROWS($B$14:B28)","v":15},"Radar","Compares values across categories in a circular orientation. Values are indicated by the distance from the center point."]
[{"$f":"ROWS($B$14:B29)","v":16},"Bubble","Compares sets of three values. Values are indicated by the size of the bubbles (filled circles). In essence X, Y and bubble size."]
[{"$f":"ROWS($B$14:B30)","v":17},"Surface","Displays value trends in three dimensions. Values are indicated by areas with colors or patterns on the surface of the chart."]
[{"$f":"ROWS($B$14:B31)","v":18}]
[{"$f":"ROWS($B$14:B32)","v":19}]
[{"$f":"ROWS($B$14:B33)","v":20}]
[]
["Chart Wizard"]
["Step 1","Chart Type","Excel provides 14 standard chart types, 75 subtypes, and 20 custom types"]
["Step 2","Source Data","Most important step. Data Range tab 1) See data range; 2) Change row/column orientation. Series tab, 1) Series shows how many data series there are (you can remove or delete); 2) Name shows the range of cells that provides a name to the data series; Values shows the range of cells that provide the numeric data points to the chart; 3) Category (X) axis labels shows the range of cells that provide the category labels. The reason this step is the most important is because the Chart Wizard does not always guess correctly and you can come here and change any source data range you want!!!"]
["Step 3","Options","1) Titles tab; 2) Axes tab - display or not the vertical and horizontal axes, change category label to time (which requires that you later right-click the axis and go to the scale tab and change the parameters for the axis); 3) Gridline tab (show or not); 4) Legend tab (show or not, move to different positions); 5) Data labels - great to add labels (series or category) - example - 1) pie category, value or % labels or 2) Histogram (Column) value labels. You must be careful with this step because it does add labels for each data point; 6) Data Table (adds data table below)."]
["Step 4","Location","Place chart as object in worksheet (good for dynamic data) or place chart as new sheet (good for printing)"]
[null,"Everything in a chart is right-clickable","Many of the coolest tricks and formatting options are not part of Chart Wizard. After the chart is done, right-click any element and point to \"Format \"THING\"\". For example, if it is an axis that you right-clicked, it will say \"Format Axis\". The dialog box that comes up does not just allow you to change formatting - it will allow to  change many parameters within the chart element."]

{"sheet":"HW Answers ==>","index":20,"n_rows":0,"n_cols":0,"rows_kept":0,"cut":false,"hidden":false,"merged":[]}

{"sheet":"P88-107","index":21,"n_rows":41,"n_cols":7,"rows_kept":41,"cut":false,"hidden":false,"merged":[]}
["Quality Control Data for TZBlazer Skis"]
["Mfg ID#","Size","Style","Date Manufactured","Production Line","Friction Coefficient ","Torsion Strength "]
[12134,174,"A","2007-11-17",1,0.82,2.21]
[12135,174,"A","2007-11-17",1,0.49,1.94]
[12139,174,"A","2007-11-17",1,0.52,2.0299999999999998]
[12140,167,"A","2007-11-17",1,0.63,2.2400000000000002]
[12142,167,"A","2007-11-17",1,0.64,2.2799999999999998]
[12144,167,"A","2007-11-17",1,1.28,2.31]
[12145,174,"A","2007-11-17",1,0.45,2.02]
[12146,167,"A","2007-11-17",1,1.1299999999999999,2.0499999999999998]
[12148,167,"E","2007-11-18",1,0.43,2.27]
[12149,174,"E","2007-11-18",1,0.47,2.31]
[12154,174,"E","2007-11-18",1,0.97,2.23]
[12156,174,"E","2007-11-18",1,0.81,2.11]
[12160,174,"E","2007-11-19",1,0.68,2.2200000000000002]
[12161,174,"E","2007-11-19",1,0.67,2.08]
[12162,181,"E","2007-11-19",1,0.95,2.0099999999999998]
[12136,181,"R","2007-11-17",2,1.32,2.35]
[12137,181,"R","2007-11-17",2,0.75,1.73]
[12138,181,"R","2007-11-17",2,0.92,2.08]
[12141,181,"R","2007-11-17",2,0.46,2.2599999999999998]
[12143,174,"R","2007-11-17",2,1.04,2.2400000000000002]
[12147,181,"A","2007-11-18",2,0.9,2.0099999999999998]
[12150,167,"A","2007-11-18",2,0.97,2]
[12151,181,"A","2007-11-18",2,0.49,2.08]
[12152,181,"A","2007-11-18",2,0.75,2.17]
[12153,167,"A","2007-11-18",2,0.3,3.22]
[12155,181,"E","2007-11-18",2,1.01,2.2400000000000002]
[12157,181,"E","2007-11-19",2,0.84,2.34]
[12158,174,"E","2007-11-19",2,0.68,2.1]
[12159,181,"A","2007-11-19",2,0.57999999999999996,2.33]
[]
["Mean",null,null,null,null,{"$f":"AVERAGE(fc)","v":{"$error":"#NAME?"}},{"$f":"AVERAGE(ts)","v":{"$error":"#NAME?"}}]
["Median",null,null,null,null,{"$f":"MEDIAN(fc)","v":{"$error":"#NAME?"}},{"$f":"MEDIAN(ts)","v":{"$error":"#NAME?"}}]
["Mode",null,null,null,null,{"$f":"MODE(fc)","v":{"$error":"#NAME?"}},{"$f":"MODE(ts)","v":{"$error":"#NAME?"}}]
["Standard Deviation",null,null,null,null,{"$f":"STDEV(fc)","v":{"$error":"#NAME?"}},{"$f":"STDEV(ts)","v":{"$error":"#NAME?"}}]
[]
["Mean",null,null,null,null,{"$f":"ROUND(AVERAGE(fc),2)","v":{"$error":"#NAME?"}},{"$f":"ROUND(AVERAGE(ts),2)","v":{"$error":"#NAME?"}}]
["Median",null,null,null,null,{"$f":"ROUND(MEDIAN(fc),2)","v":{"$error":"#NAME?"}},{"$f":"ROUND(MEDIAN(ts),2)","v":{"$error":"#NAME?"}}]
["Mode",null,null,null,null,{"$f":"ROUND(MODE(fc),2)","v":{"$error":"#NAME?"}},{"$f":"ROUND(MODE(ts),2)","v":{"$error":"#NAME?"}}]
["Standard Deviation",null,null,null,null,{"$f":"ROUND(STDEV(fc),2)","v":{"$error":"#NAME?"}},{"$f":"ROUND(STDEV(ts),2)","v":{"$error":"#NAME?"}}]

{"sheet":"P107-111","index":22,"n_rows":15,"n_cols":11,"rows_kept":15,"cut":false,"hidden":false,"merged":[]}
["Analysis of Statistical Values - Current Data vs. Historical Data"]
[null,"Friction Coefficient ",null,null,null,null,"Torsion Strength "]
["Value:","Historical","Calculated","Difference","%Difference",null,"Historical","Calculated","Difference","%Difference"]
["Mean",0.76,{"$f":"'P88-107'!F33","v":{"$error":"#NAME?"}},{"$f":"C4-B4","v":{"$error":"#NAME?"}},{"$f":"D4/B4","v":{"$error":"#NAME?"}},null,2.27,{"$f":"'P88-107'!G33","v":{"$error":"#NAME?"}},{"$f":"H4-G4","v":{"$error":"#NAME?"}},{"$f":"I4/G4","v":{"$error":"#NAME?"}}]
["Median",0.73,{"$f":"'P88-107'!F34","v":{"$error":"#NAME?"}},{"$f":"C5-B5","v":{"$error":"#NAME?"}},{"$f":"D5/B5","v":{"$error":"#NAME?"}},null,2.2400000000000002,{"$f":"'P88-107'!G34","v":{"$error":"#NAME?"}},{"$f":"H5-G5","v":{"$error":"#NAME?"}},{"$f":"I5/G5","v":{"$error":"#NAME?"}}]
["Mode",0.53,{"$f":"'P88-107'!F35","v":{"$error":"#NAME?"}},{"$f":"C6-B6","v":{"$error":"#NAME?"}},{"$f":"D6/B6","v":{"$error":"#NAME?"}},null,2.15,{"$f":"'P88-107'!G35","v":{"$error":"#NAME?"}},{"$f":"H6-G6","v":{"$error":"#NAME?"}},{"$f":"I6/G6","v":{"$error":"#NAME?"}}]
["Standard Deviation",0.27,{"$f":"'P88-107'!F36","v":{"$error":"#NAME?"}},{"$f":"C7-B7","v":{"$error":"#NAME?"}},{"$f":"D7/B7","v":{"$error":"#NAME?"}},null,0.24,{"$f":"'P88-107'!G36","v":{"$error":"#NAME?"}},{"$f":"H7-G7","v":{"$error":"#NAME?"}},{"$f":"I7/G7","v":{"$error":"#NAME?"}}]
[]
[null,null,null,null,null,null,null,null,null,null,"What does this mean?"]
[]
[null,null,null,null,null,null,null,null,null,null,"Joanna needs to use Statistics to analyze Quality data about skis so she can detect problem, try to find solution, and reduce rejects and reduce costs"]
[null,null,null,null,null,null,null,null,null,null,"High Fraction Coefficient (HFC) (poor finish)"]
[null,null,null,null,null,null,null,null,null,null,"HFC > 1.23, skis rejected"]
[null,null,null,null,null,null,null,null,null,null,"Low Torsion Strength (LTS) (not strong enough)"]
[null,null,null,null,null,null,null,null,null,null,"LTS < 2, skis rejected"]

{"sheet":"P111-112","index":23,"n_rows":56,"n_cols":9,"rows_kept":56,"cut":false,"hidden":false,"merged":[]}
[null,null,null,null,null,1,"Make sure same high standards are met with new automated machine as were with the \"by hand method\""]
[null,null,null,null,null,2,"We want bindings to only unlock at 10 lbs. or greater. Bindings that unlock at less than 10 lbs of pressure are rejected",10,"lbs."]
[null,null,null,null,null,3,"Materials of construction should not fail at temperatures above -60 Celsius. Maximum allowable failure temperature is -60 Celsius. In order not to damage the ski, failure is determined at a level when the flexibility of the material falls below a specified level","What is specified level?"]
[]
["Quality Control Data - Ski Bindings"]
["Binding ID#","Type","Date/Time","Pressure Test (Lbs)","Failure Temperature oC"]
[3423,1,"2004-12-01T08:02:00",10.141,-66.7]
[3424,1,{"$f":"C7+0.005","v":"2004-12-01T08:09:12"},10.743,-66.3]
[3425,1,{"$f":"C8+0.005","v":"2004-12-01T08:16:24"},10.487,-69.900000000000006]
[3426,1,"2004-12-01T08:23:36",11.039,-68.400000000000006]
[3427,1,"2004-12-01T08:30:48",10,-68.7]
[3428,1,"2004-12-01T08:38:00",11.531000000000001,-66]
[3429,1,"2004-12-01T08:45:12",10,-66.400000000000006]
[3430,1,"2004-12-01T08:52:24",10.32,-68.3]
[3431,1,"2004-12-01T08:59:36",10,-67.5]
[3432,1,"2004-12-01T09:06:48",10.51,-70.599999999999994]
[3433,1,"2004-12-01T09:14:00",10,-66.7]
[3434,1,"2004-12-01T09:21:12",10.426,-68]
[3435,1,"2004-12-01T09:28:24",10.099,-58.9]
[3436,1,"2004-12-01T09:35:36",10,-66.5]
[3437,1,"2004-12-01T09:42:48",12.999000000000001,-69.2]
[3438,1,{"$f":"C21+0.005","v":"2004-12-01T09:50:00"},10.118,-66.8]
[3439,2,"2004-12-01T09:57:12",10.571,-67.7]
[3440,2,"2004-12-01T10:04:24",10.135,-67.8]
[3441,2,"2004-12-01T10:11:36",10.563000000000001,-66]
[3442,2,"2004-12-01T10:18:48",10.397,-69.2]
[3443,2,"2004-12-01T10:26:00",10,-66]
[3444,2,"2004-12-01T10:33:12",10.385999999999999,-65.5]
[3445,2,"2004-12-01T10:40:24",10.31,-68.7]
[3446,2,"2004-12-01T10:47:36",10.151999999999999,-68.099999999999994]
[3447,2,"2004-12-01T10:54:48",10,-56]
[3448,2,"2004-12-01T11:02:00",9.9730000000000008,-66]
[3449,2,"2004-12-01T11:09:12",10.16,-66.7]
[3450,2,"2004-12-01T11:16:24",10.528,-67]
[3451,3,"2004-12-01T11:23:36",10,-68.099999999999994]
[3452,3,"2004-12-01T11:30:48",11.502000000000001,-66.599999999999994]
[3453,3,"2004-12-01T11:38:00",11.638,-68.5]
[3454,3,"2004-12-01T11:45:12",10.833,-59.7]
[3455,3,"2004-12-01T11:52:24",10,-66]
[3456,3,"2004-12-01T11:59:36",10.63,-66.5]
[3457,3,"2004-12-01T12:06:48",10.851000000000001,-68.599999999999994]
[3458,3,"2004-12-01T12:14:00",12.262,-66.8]
[3459,3,"2004-12-01T12:21:12",10,-69.099999999999994]
[3460,3,"2004-12-01T12:28:24",10.404,-66.2]
[3461,3,"2004-12-01T12:35:36",11.788,-69.3]
[3462,3,"2004-12-01T12:42:48",10.813000000000001,-66]
[3463,3,"2004-12-01T12:50:00",10.239000000000001,-66.599999999999994]
[3464,3,"2004-12-01T12:57:12",11.005000000000001,-66]
[3465,3,"2004-12-01T13:04:24",10.186999999999999,-69]
[3466,3,"2004-12-01T13:11:36",11.045999999999999,-67]
[3467,3,"2004-12-01T13:18:48",10.76,-66.8]
[]
[null,null,"Mean",{"$f":"AVERAGE(pt)","v":{"$error":"#NAME?"}},{"$f":"AVERAGE(ft)","v":{"$error":"#NAME?"}}]
[null,null,"Median",{"$f":"MEDIAN(pt)","v":{"$error":"#NAME?"}},{"$f":"MEDIAN(ft)","v":{"$error":"#NAME?"}}]
[null,null,"Mode",{"$f":"MODE(pt)","v":{"$error":"#NAME?"}},{"$f":"MODE(ft)","v":{"$error":"#NAME?"}}]
[null,null,"Standard Deviation",{"$f":"STDEV(pt)","v":{"$error":"#NAME?"}},{"$f":"STDEV(ft)","v":{"$error":"#NAME?"}}]

{"sheet":"P112","index":24,"n_rows":12,"n_cols":9,"rows_kept":12,"cut":false,"hidden":false,"merged":[]}
["Historical Data for Bindings as Compared to Current Data"]
[null,"Pressure Test (Lbs)",null,null,null,"Failure Temperature oC"]
[null,"Historical","Current","Difference","% Difference","Historical","Current","Difference","% Difference"]
["Mean",10.305,{"$f":"'P111-112'!D53","v":{"$error":"#NAME?"}},{"$f":"C4-B4","v":{"$error":"#NAME?"}},{"$f":"D4/B4","v":{"$error":"#NAME?"}},-63.820999999999998,{"$f":"'P111-112'!E53","v":{"$error":"#NAME?"}},{"$f":"G4-F4","v":{"$error":"#NAME?"}},{"$f":"H4/F4","v":{"$error":"#NAME?"}}]
["Median",10.221,{"$f":"'P111-112'!D54","v":{"$error":"#NAME?"}},{"$f":"C5-B5","v":{"$error":"#NAME?"}},{"$f":"D5/B5","v":{"$error":"#NAME?"}},-67.010000000000005,{"$f":"'P111-112'!E54","v":{"$error":"#NAME?"}},{"$f":"G5-F5","v":{"$error":"#NAME?"}},{"$f":"H5/F5","v":{"$error":"#NAME?"}}]
["Mode",10,{"$f":"'P111-112'!D55","v":{"$error":"#NAME?"}},{"$f":"C6-B6","v":{"$error":"#NAME?"}},{"$f":"D6/B6","v":{"$error":"#NAME?"}},-66,{"$f":"'P111-112'!E55","v":{"$error":"#NAME?"}},{"$f":"G6-F6","v":{"$error":"#NAME?"}},{"$f":"H6/F6","v":{"$error":"#NAME?"}}]
["Standard Deviation",0.80100000000000005,{"$f":"'P111-112'!D56","v":{"$error":"#NAME?"}},{"$f":"C7-B7","v":{"$error":"#NAME?"}},{"$f":"D7/B7","v":{"$error":"#NAME?"}},2.601,{"$f":"'P111-112'!E56","v":{"$error":"#NAME?"}},{"$f":"G7-F7","v":{"$error":"#NAME?"}},{"$f":"H7/F7","v":{"$error":"#NAME?"}}]
[]
["Conclusions:"]
["The pressure test came out positive, no corrections needed. Because we reject at less than 10, the fact that the mean and median went up is a good sign - a sign that the bindings hold well. The current mode is the same as the historical, but it is less then the current Mean and Median: this means that the \"tail\" (or Skew) is toward the positive side and a few large values are pulling the mean up. The current standard deviation is about 17% lower than the historical standard deviation which means that the data points are clustered more closely around the mean and that the production process is more consistent than before."]
["The failure temperature statistics are all similar to the historical ones and thus the process seems to be similar to before"]
["In the end, the new production machine seems to be the same or a bit better than the \"by hand\" process that we used to employ."]

{"sheet":"P113-115,119-124","index":25,"n_rows":50,"n_cols":10,"rows_kept":50,"cut":false,"hidden":false,"merged":[]}
["Quality Control Data for TZBlazer Skis"]
["Mfg ID#","Size","Style","Date Manufactured","Production Line","Friction Coefficient (lowest is best)","Torsion Strength (highest is best)","Ski Cost","Rank Friction Coefficient (lowest is best)","Rank Torsion Strength (highest is best)"]
[12134,174,"A","2007-11-17",1,0.82,2.21,54.5,{"$f":"RANK(F3,F$3:F$31,1)","v":18},{"$f":"RANK(G3,G$3:G$31,0)","v":15}]
[12135,174,"A","2007-11-17",1,0.49,1.94,54.5,6,28]
[12139,174,"A","2007-11-17",1,0.52,2.0299999999999998,54.5,8,23]
[12140,167,"A","2007-11-17",1,0.63,2.2400000000000002,45.5,10,10]
[12142,167,"A","2007-11-17",1,0.64,2.2799999999999998,45.5,11,7]
[12144,167,"A","2007-11-17",1,1.28,2.31,45.5,28,5]
[12145,174,"A","2007-11-17",1,0.45,2.02,54.5,3,24]
[12146,167,"A","2007-11-17",1,1.1299999999999999,2.0499999999999998,45.5,27,22]
[12148,167,"E","2007-11-18",1,0.43,2.27,55.5,2,8]
[12149,174,"E","2007-11-18",1,0.47,2.31,64.5,5,5]
[12154,174,"E","2007-11-18",1,0.97,2.23,64.5,23,13]
[12156,174,"E","2007-11-18",1,0.81,2.11,64.5,17,17]
[12160,174,"E","2007-11-19",1,0.68,2.2200000000000002,64.5,13,14]
[12161,174,"E","2007-11-19",1,0.67,2.08,64.5,12,19]
[12162,181,"E","2007-11-19",1,0.95,2.0099999999999998,70.5,22,25]
[12136,181,"R","2007-11-17",2,1.32,2.35,82.5,29,2]
[12137,181,"R","2007-11-17",2,0.75,1.73,82.5,15,29]
[12138,181,"R","2007-11-17",2,0.92,2.08,82.5,21,19]
[12141,181,"R","2007-11-17",2,0.46,2.2599999999999998,82.5,4,9]
[12143,174,"R","2007-11-17",2,1.04,2.2400000000000002,76.5,26,10]
[12147,181,"A","2007-11-18",2,0.9,2.0099999999999998,60.5,20,25]
[12150,167,"A","2007-11-18",2,0.97,2,45.5,23,27]
[12151,181,"A","2007-11-18",2,0.49,2.08,60.5,6,19]
[12152,181,"A","2007-11-18",2,0.75,2.17,60.5,15,16]
[12153,167,"A","2007-11-18",2,0.3,3.22,45.5,1,1]
[12155,181,"E","2007-11-18",2,1.01,2.2400000000000002,70.5,25,10]
[12157,181,"E","2007-11-19",2,0.84,2.34,70.5,19,3]
[12158,174,"E","2007-11-19",2,0.68,2.1,64.5,13,18]
[12159,181,"A","2007-11-19",2,0.57999999999999996,2.33,70.5,9,4]
[]
["Rejected ==>",null,null,null,null,{"$f":"COUNTIF(F$3:F$31,F37)","v":2},{"$f":"COUNTIF(G$3:G$31,G37)","v":2}]
[]
[null,null,null,null,null,"Assumptions"]
[null,null,null,null,null,"hurdle for FC","hurdle for TS"]
[null,null,null,null,null,{"$f":"\">\"&F38","v":">1.23"},{"$f":"\"<\"&G38","v":"<2"}]
[null,null,null,null,null,1.23,2]
[]
[null,null,null,null,null,null,1.75,1.8]
[null,null,null,null,null,null,1.2,2.5]
[null,null,null,null,null,null,0.7,1.6]
[null,null,null,null,null,null,1.29,3]
[null,null,null,null,null,null,0.2,4]
[]
[null,null,null,null,null,"Count rejected",{"$f":"COUNTIF(G$40:G$44,F37)","v":2},{"$f":"COUNTIF(H$40:H$44,G37)","v":2}]
[]
[null,null,null,null,null,"Count Total Rejected",null,{"$f":"COUNTIF(G40:G44,F37)+COUNTIF(H40:H44,G37)-SUM(IF(G40:G44>F38,IF(H40:H44<G38,1,0)))","v":3}]
[]
[null,null,null,null,null,"Count non-contiguous ranges",null,{"$f":"COUNTIF(E3:E31,\">\"&1)+COUNTIF(C3:C31,\"a\")","v":28}]

{"sheet":"P116-118","index":26,"n_rows":8,"n_cols":5,"rows_kept":8,"cut":false,"hidden":false,"merged":[[0,0,0,4],[1,1,1,2],[1,3,1,4]]}
["Analysis of QC Data Extreme Values"]
[null,"Top 5 (Highest)",null,"Bottom 5 (Lowest)"]
[null,"Friction Coefficient ","Torsion Strength ","Friction Coefficient ","Torsion Strength "]
[1,{"$f":"LARGE('P113-115,119-124'!F$3:F$31,$A4)","v":1.32},{"$f":"LARGE('P113-115,119-124'!G$3:G$31,$A4)","v":3.22},{"$f":"SMALL('P113-115,119-124'!F$3:F$31,$A4)","v":0.3},{"$f":"SMALL('P113-115,119-124'!G$3:G$31,$A4)","v":1.73}]
[2,{"$f":"LARGE('P113-115,119-124'!F$3:F$31,$A5)","v":1.28},{"$f":"LARGE('P113-115,119-124'!G$3:G$31,$A5)","v":2.35},{"$f":"SMALL('P113-115,119-124'!F$3:F$31,$A5)","v":0.43},{"$f":"SMALL('P113-115,119-124'!G$3:G$31,$A5)","v":1.94}]
[3,{"$f":"LARGE('P113-115,119-124'!F$3:F$31,$A6)","v":1.1299999999999999},{"$f":"LARGE('P113-115,119-124'!G$3:G$31,$A6)","v":2.34},{"$f":"SMALL('P113-115,119-124'!F$3:F$31,$A6)","v":0.45},{"$f":"SMALL('P113-115,119-124'!G$3:G$31,$A6)","v":2}]
[4,{"$f":"LARGE('P113-115,119-124'!F$3:F$31,$A7)","v":1.04},{"$f":"LARGE('P113-115,119-124'!G$3:G$31,$A7)","v":2.33},{"$f":"SMALL('P113-115,119-124'!F$3:F$31,$A7)","v":0.46},{"$f":"SMALL('P113-115,119-124'!G$3:G$31,$A7)","v":2.0099999999999998}]
[5,{"$f":"LARGE('P113-115,119-124'!F$3:F$31,$A8)","v":1.01},{"$f":"LARGE('P113-115,119-124'!G$3:G$31,$A8)","v":2.31},{"$f":"SMALL('P113-115,119-124'!F$3:F$31,$A8)","v":0.47},{"$f":"SMALL('P113-115,119-124'!G$3:G$31,$A8)","v":2.0099999999999998}]

{"sheet":"P124-130","index":27,"n_rows":39,"n_cols":10,"rows_kept":39,"cut":false,"hidden":false,"merged":[]}
["Quality Control Data for TZBlazer Skis"]
["Mfg ID#","Size","Style","Date Manufactured","Production Line","Friction Coefficient (lowest is best)","Torsion Strength (highest is best)","Ski Cost","Rank Friction Coefficient (lowest is best)","Rank Torsion Strength (highest is best)"]
[12134,174,"A","2007-11-17",1,0.82,2.21,54.5,{"$f":"IF(F3=\"\",\"\",RANK(F3,F$3:F$31,1))","v":16},15]
[12135,174,"A","2007-11-17",1,null,1.94,54.5,"",2]
[12139,174,"A","2007-11-17",1,0.52,2.0299999999999998,54.5,7,7]
[12140,167,"A","2007-11-17",1,0.63,2.2400000000000002,45.5,9,18]
[12142,167,"A","2007-11-17",1,0.64,2.2799999999999998,45.5,10,23]
[12144,167,"A","2007-11-17",1,1.28,null,45.5,26,""]
[12145,174,"A","2007-11-17",1,0.45,2.02,54.5,3,6]
[12146,167,"A","2007-11-17",1,1.1299999999999999,2.0499999999999998,45.5,25,8]
[12148,167,"E","2007-11-18",1,0.43,2.27,55.5,2,22]
[12149,174,"E","2007-11-18",1,0.47,2.31,64.5,5,24]
[12154,174,"E","2007-11-18",1,0.97,2.23,64.5,21,17]
[12156,174,"E","2007-11-18",1,0.81,2.11,64.5,15,13]
[12160,174,"E","2007-11-19",1,0.68,2.2200000000000002,64.5,12,16]
[12161,174,"E","2007-11-19",1,0.67,2.08,64.5,11,9]
[12162,181,"E","2007-11-19",1,0.95,2.0099999999999998,70.5,20,4]
[12136,181,"R","2007-11-17",2,1.32,null,82.5,27,""]
[12137,181,"R","2007-11-17",2,null,1.73,82.5,"",1]
[12138,181,"R","2007-11-17",2,0.92,2.08,82.5,19,9]
[12141,181,"R","2007-11-17",2,0.46,2.2599999999999998,82.5,4,21]
[12143,174,"R","2007-11-17",2,1.04,2.2400000000000002,76.5,24,18]
[12147,181,"A","2007-11-18",2,0.9,2.0099999999999998,60.5,18,4]
[12150,167,"A","2007-11-18",2,0.97,2,45.5,21,3]
[12151,181,"A","2007-11-18",2,0.49,2.08,60.5,6,9]
[12152,181,"A","2007-11-18",2,0.75,2.17,60.5,14,14]
[12153,167,"A","2007-11-18",2,0.3,3.22,45.5,1,27]
[12155,181,"E","2007-11-18",2,1.01,2.2400000000000002,70.5,23,18]
[12157,181,"E","2007-11-19",2,0.84,2.34,70.5,17,26]
[12158,174,"E","2007-11-19",2,0.68,2.1,64.5,12,12]
[12159,181,"A","2007-11-19",2,0.57999999999999996,2.33,70.5,8,25]
[]
["Rejected ==>",null,null,null,null,{"$f":"COUNTIF('P113-115,119-124'!F$3:F$31,'P113-115,119-124'!F37)","v":2},{"$f":"COUNTIF('P113-115,119-124'!G$3:G$31,'P113-115,119-124'!G37)","v":2},"Sum of Costs for Rejects"]
["Cost of Rejection ==>",null,null,null,null,{"$f":"SUMIF(F$3:F$31,F$38,$H$3:$H$31)","v":128},{"$f":"SUMIF(G$3:G$31,G$38,$H$3:$H$31)","v":137},{"$f":"SUM(F34:G34)","v":265},"or",{"$f":"SUMIF(F3:F31,F38,H3:H31)+SUMIF(G3:G31,G38,H3:H31)","v":265}]
[]
[null,null,null,null,null,"Assumptions"]
[null,null,null,null,null,"hurdle for FC","hurdle for TS"]
[null,null,null,null,null,{"$f":"\">\"&F39","v":">1.23"},{"$f":"\"<\"&G39","v":"<2"}]
[null,null,null,null,null,1.23,2]

{"sheet":"P130","index":28,"n_rows":54,"n_cols":11,"rows_kept":54,"cut":false,"hidden":false,"merged":[[0,0,0,5]]}
["Quality Control Data - Ski Bindings"]
["Inspection#","Type","Date/Time","Pressure Test (Lbs) - above 10 lbs is good, below 10 lbs, binding rejected (pt)","Material Failure Temperature oC - below -60 is good, above -60 binding rejected (ft)","Component Value","pt Rank","ft Rank"]
[3423,1,"2004-12-01T08:02:00",10.141,-66.7,33.5,{"$f":"RANK(D3,D$3:D$47,0)","v":33},{"$f":"RANK(E3,E$3:E$47,1)","v":25}]
[3424,1,{"$f":"C3+0.005","v":"2004-12-01T08:09:12"},10.743,-66.3,33.5,14,33]
[3425,1,"2004-12-01T08:16:24",10.487,-69.900000000000006,41.05,20,2]
[3426,1,"2004-12-01T08:23:36",11.039,-68.400000000000006,33.5,9,12]
[3427,1,"2004-12-01T08:30:48",10,-68.7,33.5,36,8]
[3428,1,"2004-12-01T08:38:00",11.531000000000001,-66,41.05,5,35]
[3429,1,"2004-12-01T08:45:12",10,-66.400000000000006,41.05,36,32]
[3430,1,"2004-12-01T08:52:24",10.32,-68.3,33.5,27,13]
[3431,1,"2004-12-01T08:59:36",10,-67.5,33.5,36,19]
[3432,1,"2004-12-01T09:06:48",10.51,-70.599999999999994,33.5,19,1]
[3433,1,"2004-12-01T09:14:00",10,-66.7,41.05,36,25]
[3434,1,"2004-12-01T09:21:12",10.426,-68,41.05,22,16]
[3435,1,"2004-12-01T09:28:24",10.387,-58.9,41.05,25,44]
[3436,1,"2004-12-01T09:35:36",10,-66.5,41.05,36,30]
[3437,1,"2004-12-01T09:42:48",12.999000000000001,-69.2,41.05,1,4]
[3438,1,"2004-12-01T09:50:00",10.118,-66.8,41.05,35,22]
[3439,2,"2004-12-01T09:57:12",10.571,-67.7,64,16,18]
[3440,2,"2004-12-01T10:04:24",10.135,-67.8,63.09,34,17]
[3441,2,"2004-12-01T10:11:36",10.563000000000001,-66,63.09,17,35]
[3442,2,"2004-12-01T10:18:48",10.397,-69.2,64,24,4]
[3443,2,"2004-12-01T10:26:00",10,-66,64,36,35]
[3444,2,"2004-12-01T10:33:12",10.385999999999999,-65.5,64,26,41]
[3445,2,"2004-12-01T10:40:24",10.31,-68.7,63.09,28,8]
[3446,2,"2004-12-01T10:47:36",10.151999999999999,-68.099999999999994,63.09,32,14]
[3447,2,"2004-12-01T10:54:48",10.725,-56,63.09,15,45]
[3448,2,"2004-12-01T11:02:00",9.9730000000000008,-63,63.09,45,42]
[3449,2,"2004-12-01T11:09:12",10.16,-66.7,55.17,31,25]
[3450,2,"2004-12-01T11:16:24",10.528,-67,55.17,18,20]
[3451,3,"2004-12-01T11:23:36",10,-68.099999999999994,22.09,36,14]
[3452,3,"2004-12-01T11:30:48",11.502000000000001,-66.599999999999994,22.09,6,28]
[3453,3,"2004-12-01T11:38:00",11.638,-68.5,22.09,4,11]
[3454,3,"2004-12-01T11:45:12",10.43,-59.7,22.09,21,43]
[3455,3,"2004-12-01T11:52:24",10,-66,22.09,36,35]
[3456,3,"2004-12-01T11:59:36",11.321,-66.5,22.09,7,30]
[3457,4,"2004-12-01T12:06:48",10.851000000000001,-68.599999999999994,32.08,11,10]
[3458,4,"2004-12-01T12:14:00",12.262,-66.8,32.08,2,22]
[3459,4,"2004-12-01T12:21:12",10,-69.099999999999994,39.950000000000003,36,6]
[3460,4,"2004-12-01T12:28:24",10.404,-66.2,27.39,23,34]
[3461,4,"2004-12-01T12:35:36",11.788,-69.3,27.39,3,3]
[3462,4,"2004-12-01T12:42:48",10.813000000000001,-66,27.39,12,35]
[3463,4,"2004-12-01T12:50:00",10.239000000000001,-66.599999999999994,27.39,29,28]
[3464,5,"2004-12-01T12:57:12",11.005000000000001,-66,92.03,10,35]
[3465,5,"2004-12-01T13:04:24",10.186999999999999,-69,92.03,30,7]
[3466,5,"2004-12-01T13:11:36",11.045999999999999,-67,92.03,8,20]
[3467,5,"2004-12-01T13:18:48",10.76,-66.8,92.03,13,22]
[null,null,null,null,null,"Sum of Rejects",null,null,null,null,"Sum of Rejects"]
[null,null,"Rejected ==>",{"$f":"COUNTIF(D$3:D$47,D53)","v":1},{"$f":"COUNTIF(E$3:E$47,E53)","v":3},{"$f":"SUMIF(D3:D47,D53,F3:F47)+SUMIF(E3:E47,E53,F3:F47)","v":189.32},null,null,null,null,{"$f":"SUMIF(D3:D47,D53,F3:F47)+SUMIF(E3:E47,E53,F3:F47)-SUM(IF(D3:D47<D54,IF(E3:E47>E54,F3:F47)))","v":189.32}]
[]
[null,null,"Assumptions"]
[null,null,null,"Hurdle to reject given pt","Hurdle to reject given ft"]
[null,null,null,{"$f":"\"<\"&D54","v":"<10"},{"$f":"\">\"&E54","v":">-60"}]
[null,null,null,10,-60]

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["Analyze Extremes in Pressure and Temperature"]
[null,"Top 5 Highest",null,"Top 5 Lowest"]
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[null,null,null,null,null,null,null,"Style"]
["Time Data for Quality Control Testing - Per Ski",null,null,null,null,null,null,"R"]
[null,null,"Actual Time in Minutes",null,"Quality Inspector Wage",null,null,"E"]
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[2346,"R",1,1,{"$f":"SUM(C6:D6)/60*E$4","v":1.1666666666666667}]
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[2350,"R",1.5,5,3.791666666666667]
[2351,"R",null,null,{"$f":"SUM(C11:D11)/60*E$4","v":0}]
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[2353,"R",1,4,2.9166666666666665]
[2354,"E",2,1,1.75]
[2355,"R",1.5,1.5,1.75]
[2356,"A",1,7,4.666666666666667]
[2357,"R",2,3.5,3.208333333333333]
[2358,"E",1,4.5,3.208333333333333]
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[2363,"A",1.5,6,4.375]
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[2366,"R",1,1,1.1666666666666667]
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[2368,"A",1,7.5,4.958333333333333]
[2369,"A",1,3,2.3333333333333335]
[2370,"E",1,5,3.5]
[2371,"A",2,6.5,4.958333333333333]
[2372,"E",1.5,6,4.375]
[2373,"R",1.5,4.5,3.5]
[2374,"R",1,2,1.75]
[2375,"A",1.5,2.5,2.3333333333333335]
[2376,"R",1,1,1.1666666666666667]
[2377,"A",2.5,2.5,2.9166666666666665]
[2378,"E",1,3.5,2.625]
[2379,"R",2,1,1.75]
[2380,"R",1,2.5,2.0416666666666665]
[2381,"R",1.5,5,3.791666666666667]
[2382,"R",2,3.5,3.208333333333333]
[2383,"R",1.5,4,3.208333333333333]
[2384,"A",2.5,7,5.5416666666666661]
[2385,"E",1,2.5,2.0416666666666665]
[2386,"A",3,3.5,3.791666666666667]
[2387,"E",1.5,5.5,4.083333333333333]
[2388,"R",1.5,4,3.208333333333333]
[2389,"E",1.5,2.5,2.3333333333333335]
[2390,"E",2.5,6,4.958333333333333]
[2391,"R",1,1,1.1666666666666667]
[2392,"R",1,1.5,1.4583333333333333]
[2393,"E",1.5,5.5,4.083333333333333]
[2394,"E",2,2,2.3333333333333335]
[2395,"A",3.5,1.5,2.9166666666666665]
[2396,"R",2,1,1.75]
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[2398,"R",1,1,1.1666666666666667]
[2399,"R",1,3,2.3333333333333335]
[2400,"R",1,1.5,1.4583333333333333]
[2401,"R",1.5,4.5,3.5]
[2402,"A",2.5,5.5,4.666666666666667]
[2403,"A",1,7,4.666666666666667]
[2404,"E",1,2,1.75]
[2405,"R",1,5,3.5]
[2406,"A",4,7,6.4166666666666661]
[2407,"E",1.5,4,3.208333333333333]
[2408,"A",1,3.5,2.625]
[2409,"R",2,1,1.75]
[2410,"E",1.5,1,{"$f":"SUM(C70:D70)/60*E$4","v":1.4583333333333333}]
[2411,"R",1,4.5,3.208333333333333]
[2412,"E",3,1,2.3333333333333335]
[2413,"R",2,1,1.75]
[2414,"A",1,4.5,3.208333333333333]
[2415,"E",1,5,3.5]
[2416,"R",1,3.5,2.625]
[2417,"R",1,2.5,2.0416666666666665]
[2418,"R",1,3,2.3333333333333335]
[2419,"R",2,1,1.75]
[2420,"R",1,1,1.1666666666666667]
[2421,"E",1,5.5,3.791666666666667]
[2422,"R",1,1,1.1666666666666667]
[2423,"R",1,1,1.1666666666666667]
[2424,"R",1.5,1,1.4583333333333333]
[2425,"R",1,1.5,1.4583333333333333]
[2426,"R",1,4,2.9166666666666665]
[2427,"A",2,3.5,3.208333333333333]
[2428,"A",3.5,1.5,2.9166666666666665]
[2429,"R",1.5,2.5,2.3333333333333335]
[2430,"E",2.5,6,4.958333333333333]
[2431,"A",2.5,3.5,3.5]
[2432,"R",1,2,1.75]
[2433,"A",1,2,1.75]
[2434,"R",1,4,2.9166666666666665]
[2435,"R",1.5,2,2.0416666666666665]
[2436,"A",2.5,4.5,4.083333333333333]
[2437,"R",1.5,1,1.4583333333333333]
[2438,"R",1.5,1,1.4583333333333333]
[2439,"A",1,5.5,3.791666666666667]
[2440,"R",1,5,3.5]
[2441,"R",1,2,1.75]
[2442,"A",3.5,5,4.958333333333333]
[2443,"E",1,4,2.9166666666666665]
[2444,"A",1.5,1,1.4583333333333333]
[]
[null,"Total",{"$f":"SUM(C5:C104)","v":154.5},{"$f":"SUM(D5:D104)","v":321.5},{"$f":"SUM(E5:E104)","v":277.66666666666663}]
[null,"Average",{"$f":"AVERAGE(C5:C104)","v":1.5606060606060606},{"$f":"AVERAGE(D5:D104)","v":3.2474747474747474},{"$f":"AVERAGE(E5:E104)","v":2.7766666666666664}]
[null,"Standard Deviation",{"$f":"STDEV(C5:C104)","v":0.72938584478665269},{"$f":"STDEV(D5:D104)","v":1.8549076347730837},{"$f":"STDEV(E5:E104)","v":1.2273126318490732}]
[]
[null,"Sum of average time",{"$f":"SUM(C107:D107)","v":4.808080808080808},{"$f":"E4","v":35},{"$f":"C110/60*D110","v":2.8047138047138045}]

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[null,null,null,null,null,null,null,"Style"]
["Time Data for Quality Control Testing - Per Ski",null,null,null,null,null,null,"R"]
[null,null,"Actual Time in Minutes",null,"Quality Inspector Wage",null,null,"E"]
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[2346,"R",1,1,{"$f":"SUM(C6:D6)/60*E$4","v":1.5}]
[2347,"R",1,3,3]
[2348,"R",2,5,5.25]
[2349,"R",1,1.5,1.875]
[2350,"R",1.5,5,4.875]
[2351,"R",null,null,{"$f":"SUM(C11:D11)/60*E$4","v":0}]
[2352,"E",2.5,3.5,4.5]
[2353,"R",1,4,3.75]
[2354,"E",2,1,2.25]
[2355,"R",1.5,1.5,2.25]
[2356,"A",1,7,6]
[2357,"R",2,3.5,4.125]
[2358,"E",1,4.5,4.125]
[2359,"A",3,2,3.75]
[2360,"A",3.5,3,4.875]
[2361,"R",2,4.5,4.875]
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[2363,"A",1.5,6,5.625]
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[2371,"A",2,6.5,6.375]
[2372,"E",1.5,6,5.625]
[2373,"R",1.5,4.5,4.5]
[2374,"R",1,2,2.25]
[2375,"A",1.5,2.5,3]
[2376,"R",1,1,1.5]
[2377,"A",2.5,2.5,3.75]
[2378,"E",1,3.5,3.375]
[2379,"R",2,1,2.25]
[2380,"R",1,2.5,2.625]
[2381,"R",1.5,5,4.875]
[2382,"R",2,3.5,4.125]
[2383,"R",1.5,4,4.125]
[2384,"A",2.5,7,7.125]
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[2390,"E",2.5,6,6.375]
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[2392,"R",1,1.5,1.875]
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[2406,"A",4,7,8.25]
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[2413,"R",2,1,2.25]
[2414,"A",1,4.5,4.125]
[2415,"E",1,5,4.5]
[2416,"R",1,3.5,3.375]
[2417,"R",1,2.5,2.625]
[2418,"R",1,3,3]
[2419,"R",2,1,2.25]
[2420,"R",1,1,1.5]
[2421,"E",1,5.5,4.875]
[2422,"R",1,1,1.5]
[2423,"R",1,1,1.5]
[2424,"R",1.5,1,1.875]
[2425,"R",1,1.5,1.875]
[2426,"R",1,4,3.75]
[2427,"A",2,3.5,4.125]
[2428,"A",3.5,1.5,3.75]
[2429,"R",1.5,2.5,3]
[2430,"E",2.5,6,6.375]
[2431,"A",2.5,3.5,4.5]
[2432,"R",1,2,2.25]
[2433,"A",1,2,2.25]
[2434,"R",1,4,3.75]
[2435,"R",1.5,2,2.625]
[2436,"A",2.5,4.5,5.25]
[2437,"R",1.5,1,1.875]
[2438,"R",1.5,1,1.875]
[2439,"A",1,5.5,4.875]
[2440,"R",1,5,4.5]
[2441,"R",1,2,2.25]
[2442,"A",3.5,5,6.375]
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[]
[null,"Total",{"$f":"SUM(C5:C104)","v":154.5},{"$f":"SUM(D5:D104)","v":321.5},{"$f":"SUM(E5:E104)","v":357}]
[null,"Average",{"$f":"AVERAGE(C5:C104)","v":1.5606060606060606},{"$f":"AVERAGE(D5:D104)","v":3.2474747474747474},{"$f":"AVERAGE(E5:E104)","v":3.57}]
[null,"Standard Deviation",{"$f":"STDEV(C5:C104)","v":0.72938584478665269},{"$f":"STDEV(D5:D104)","v":1.8549076347730837},{"$f":"STDEV(E5:E104)","v":1.57797338380595}]
[]
[null,"Sum of average time",{"$f":"SUM(C107:D107)","v":4.808080808080808},{"$f":"E4","v":45},{"$f":"C110/60*D110","v":3.606060606060606}]

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["Time Data for Quality Control Testing - Per Ski"]
[null,null,"Actual Time in Minutes",null,"Quality Inspector Wage"]
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[2347,"R",1,3,1.8907563025210083]
[2348,"R",2,5,3.3088235294117645]
[2349,"R",1,1.5,1.1817226890756301]
[2350,"R",1.5,5,3.0724789915966388]
[2351,"R",null,null,0]
[2352,"E",2.5,3.5,2.8361344537815127]
[2353,"R",1,4,2.3634453781512601]
[2354,"E",2,1,1.4180672268907564]
[2355,"R",1.5,1.5,1.4180672268907564]
[2356,"A",1,7,3.7815126050420167]
[2357,"R",2,3.5,2.5997899159663862]
[2358,"E",1,4.5,2.5997899159663862]
[2359,"A",3,2,2.3634453781512601]
[2360,"A",3.5,3,3.0724789915966388]
[2361,"R",2,4.5,3.0724789915966388]
[2362,"A",1,1,0.94537815126050417]
[2363,"A",1.5,6,3.5451680672268906]
[2364,"R",1,4.5,2.5997899159663862]
[2365,"E",2,4.5,3.0724789915966388]
[2366,"R",1,1,0.94537815126050417]
[2367,"A",1,1.5,1.1817226890756301]
[2368,"A",1,7.5,4.0178571428571423]
[2369,"A",1,3,1.8907563025210083]
[2370,"E",1,5,2.8361344537815127]
[2371,"A",2,6.5,4.0178571428571423]
[2372,"E",1.5,6,3.5451680672268906]
[2373,"R",1.5,4.5,2.8361344537815127]
[2374,"R",1,2,1.4180672268907564]
[2375,"A",1.5,2.5,1.8907563025210083]
[2376,"R",1,1,0.94537815126050417]
[2377,"A",2.5,2.5,2.3634453781512601]
[2378,"E",1,3.5,2.1271008403361344]
[2379,"R",2,1,1.4180672268907564]
[2380,"R",1,2.5,1.6544117647058822]
[2381,"R",1.5,5,3.0724789915966388]
[2382,"R",2,3.5,2.5997899159663862]
[2383,"R",1.5,4,2.5997899159663862]
[2384,"A",2.5,7,4.4905462184873945]
[2385,"E",1,2.5,1.6544117647058822]
[2386,"A",3,3.5,3.0724789915966388]
[2387,"E",1.5,5.5,3.3088235294117645]
[2388,"R",1.5,4,2.5997899159663862]
[2389,"E",1.5,2.5,1.8907563025210083]
[2390,"E",2.5,6,4.0178571428571423]
[2391,"R",1,1,0.94537815126050417]
[2392,"R",1,1.5,1.1817226890756301]
[2393,"E",1.5,5.5,3.3088235294117645]
[2394,"E",2,2,1.8907563025210083]
[2395,"A",3.5,1.5,2.3634453781512601]
[2396,"R",2,1,1.4180672268907564]
[2397,"R",1,5,2.8361344537815127]
[2398,"R",1,1,0.94537815126050417]
[2399,"R",1,3,1.8907563025210083]
[2400,"R",1,1.5,1.1817226890756301]
[2401,"R",1.5,4.5,2.8361344537815127]
[2402,"A",2.5,5.5,3.7815126050420167]
[2403,"A",1,7,3.7815126050420167]
[2404,"E",1,2,1.4180672268907564]
[2405,"R",1,5,2.8361344537815127]
[2406,"A",4,7,5.1995798319327724]
[2407,"E",1.5,4,2.5997899159663862]
[2408,"A",1,3.5,2.1271008403361344]
[2409,"R",2,1,{"$f":"SUM(C68:D68)/60*E$3","v":1.4180672268907564}]
[2410,"E",1.5,1,1.1817226890756301]
[2411,"R",1,4.5,2.5997899159663862]
[2412,"E",3,1,1.8907563025210083]
[2413,"R",2,1,1.4180672268907564]
[2414,"A",1,4.5,2.5997899159663862]
[2415,"E",1,5,2.8361344537815127]
[2416,"R",1,3.5,2.1271008403361344]
[2417,"R",1,2.5,1.6544117647058822]
[2418,"R",1,3,1.8907563025210083]
[2419,"R",2,1,1.4180672268907564]
[2420,"R",1,1,0.94537815126050417]
[2421,"E",1,5.5,3.0724789915966388]
[2422,"R",1,1,0.94537815126050417]
[2423,"R",1,1,0.94537815126050417]
[2424,"R",1.5,1,1.1817226890756301]
[2425,"R",1,1.5,1.1817226890756301]
[2426,"R",1,4,2.3634453781512601]
[2427,"A",2,3.5,2.5997899159663862]
[2428,"A",3.5,1.5,2.3634453781512601]
[2429,"R",1.5,2.5,1.8907563025210083]
[2430,"E",2.5,6,4.0178571428571423]
[2431,"A",2.5,3.5,2.8361344537815127]
[2432,"R",1,2,1.4180672268907564]
[2433,"A",1,2,1.4180672268907564]
[2434,"R",1,4,2.3634453781512601]
[2435,"R",1.5,2,1.6544117647058822]
[2436,"A",2.5,4.5,3.3088235294117645]
[2437,"R",1.5,1,1.1817226890756301]
[2438,"R",1.5,1,1.1817226890756301]
[2439,"A",1,5.5,3.0724789915966388]
[2440,"R",1,5,2.8361344537815127]
[2441,"R",1,2,{"$f":"SUM(C100:D100)/60*E$3","v":1.4180672268907564}]
[2442,"A",3.5,5,{"$f":"SUM(C101:D101)/60*E$3","v":4.0178571428571423}]
[2443,"E",1,4,{"$f":"SUM(C102:D102)/60*E$3","v":2.3634453781512601}]
[2444,"A",1.5,1,{"$f":"SUM(C103:D103)/60*E$3","v":1.1817226890756301}]
[]
[null,"Total",{"$f":"SUM(C4:C103)","v":154.5},{"$f":"SUM(D4:D103)","v":321.5},{"$f":"SUM(E4:E103)","v":225.00000000000009}]
[null,"Average",{"$f":"AVERAGE(C4:C103)","v":1.5606060606060606},{"$f":"AVERAGE(D4:D103)","v":3.2474747474747474},{"$f":"AVERAGE(E4:E103)","v":2.2500000000000009}]
[null,"Standard Deviation",{"$f":"STDEV(C4:C103)","v":0.72938584478665269},{"$f":"STDEV(D4:D103)","v":1.8549076347730837},{"$f":"STDEV(E4:E103)","v":0.99452104021382992}]
[]
[null,"Sum of average time",{"$f":"SUM(C106:D106)","v":4.808080808080808},{"$f":"E3","v":28.361344537815125},{"$f":"C109/60*D109","v":2.2727272727272725}]

{"sheet":"P142-144","index":33,"n_rows":10,"n_cols":5,"rows_kept":10,"cut":false,"hidden":false,"merged":[]}
["Summary- By Ski Type"]
["Style","Quantity of Skis Tested","Average Friction Test Time","Average Torsion Test Time","Average Cost"]
[{"$f":"A8","v":"R"},{"$f":"COUNTIF('P131-138'!B$5:B$104,'P142-144'!A3)","v":52},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A3,'P131-138'!C$5:C$104)/COUNTIF('P131-138'!$B$5:$B$104,$A3)","v":1.2692307692307692},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A3,'P131-138'!D$5:D$104)/COUNTIF('P131-138'!$B$5:$B$104,$A3)","v":2.5480769230769229},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A3,'P131-138'!E$5:E$104)/COUNTIF('P131-138'!$B$5:$B$104,$A3)","v":2.2267628205128203}]
[{"$f":"A9","v":"E"},{"$f":"COUNTIF('P131-138'!B$5:B$104,'P142-144'!A4)","v":21},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A4,'P131-138'!C$5:C$104)/COUNTIF('P131-138'!$B$5:$B$104,$A4)","v":1.5952380952380953},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A4,'P131-138'!D$5:D$104)/COUNTIF('P131-138'!$B$5:$B$104,$A4)","v":3.8333333333333335},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A4,'P131-138'!E$5:E$104)/COUNTIF('P131-138'!$B$5:$B$104,$A4)","v":3.1666666666666674}]
[{"$f":"A10","v":"A"},{"$f":"COUNTIF('P131-138'!B$5:B$104,'P142-144'!A5)","v":27},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A5,'P131-138'!C$5:C$104)/COUNTIF('P131-138'!$B$5:$B$104,$A5)","v":2.0370370370370372},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A5,'P131-138'!D$5:D$104)/COUNTIF('P131-138'!$B$5:$B$104,$A5)","v":4.0185185185185182},{"$f":"SUMIF('P131-138'!$B$5:$B$104,$A5,'P131-138'!E$5:E$104)/COUNTIF('P131-138'!$B$5:$B$104,$A5)","v":3.5324074074074057}]
[]
["Style","Quantity of Skis Tested","Average Friction Test Time","Average Torsion Test Time","Average Cost"]
[{"$f":"'P138-139'!H2","v":"R"},{"$f":"COUNTIF('P139-141'!$B$4:$B$103,A8)","v":52},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A8,'P131-138'!C$5:C$104)","v":1.2941176470588236},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A8,'P131-138'!D$5:D$104)","v":2.5980392156862746},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A8,'P131-138'!E$5:E$104)","v":2.2267628205128203}]
[{"$f":"'P138-139'!H3","v":"E"},{"$f":"COUNTIF('P139-141'!$B$4:$B$103,A9)","v":21},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A9,'P131-138'!C$5:C$104)","v":1.5952380952380953},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A9,'P131-138'!D$5:D$104)","v":3.8333333333333335},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A9,'P131-138'!E$5:E$104)","v":3.1666666666666674}]
[{"$f":"'P138-139'!H4","v":"A"},{"$f":"COUNTIF('P139-141'!$B$4:$B$103,A10)","v":27},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A10,'P131-138'!C$5:C$104)","v":2.0370370370370372},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A10,'P131-138'!D$5:D$104)","v":4.0185185185185182},{"$f":"AVERAGEIF('P131-138'!$B$5:$B$104,$A10,'P131-138'!E$5:E$104)","v":3.5324074074074057}]

{"sheet":"P144-149","index":34,"n_rows":102,"n_cols":8,"rows_kept":102,"cut":false,"hidden":false,"merged":[]}
["Ski Return Cost Simulation",null,null,null,null,"Costs of not inspecting"]
["Style","Return Cost","Probability of Failure","Probable Cost",null,"Handling and returning the defective ski"]
[{"$f":"RANDBETWEEN(H$11,H$13)","v":3},{"$f":"RANDBETWEEN(G$4,H$4)+ROUND(RAND(),2)","v":176.96},{"$f":"G$5+RAND()*(H$5-G$5)","v":4.9820754070731721E-2},{"$f":"ROUND(B3*C3,2)","v":8.82},null,"Getting new ski to customer"]
[{"$f":"RANDBETWEEN(H$11,H$13)","v":2},{"$f":"RANDBETWEEN(G$4,H$4)+ROUND(RAND(),2)","v":87.56},{"$f":"G$5+RAND()*(H$5-G$5)","v":3.815889105575912E-2},{"$f":"ROUND(B4*C4,2)","v":3.34},null,"Costs vary between",25,200]
[3,132.87,3.7465457866442411E-2,4.9800000000000004,null,"Ski Failure rate varies between",0.03,0.05]
[3,57.02,3.5257226449576698E-2,2.0099999999999998,null,"Number of Skis",100]
[3,200,4.5469500725197003E-2,9.09,null,"Estimation of Cost of not inspecting =",{"$f":"AVERAGE(G4:H4)*AVERAGE(G5:H5)*G6","v":450}]
[2,150.71,3.367593460570225E-2,5.08,null,{"$f":"'P131-138'!A2&\" \"&'P131-138'!B106","v":"Time Data for Quality Control Testing - Per Ski Total"},{"$f":"'P131-138'!E106","v":277.66666666666663}]
[3,179.6,3.9852192669657747E-2,7.16]
[2,98,4.6134976426617041E-2,4.5199999999999996,null,"Simulated probable Costs for by Ski Type","Style"]
[3,106.12,3.4577701759823151E-2,3.67,null,{"$f":"SUMIF(A$3:A$102,H11,D$3:D$102)","v":150.60000000000005},"A",1]
[1,40.65,3.0941062778356142E-2,1.26,null,{"$f":"SUMIF(A$3:A$102,H12,D$3:D$102)","v":123.21999999999997},"E",2]
[2,44.48,4.883558513052931E-2,2.17,null,{"$f":"SUMIF(A$3:A$102,H13,D$3:D$102)","v":171.01999999999998},"R",3]
[1,71.959999999999994,4.9638127765055148E-2,3.57,null,{"$f":"SUM(F11:F13)","v":444.84000000000003}]
[2,88.99,4.7255593323166319E-2,4.21]
[2,152.58000000000001,3.1216261760756776E-2,4.76,null,"Can costs be improved given the large variation in Quality Inspection Costs?"]
[3,151.58000000000001,4.7003387686613454E-2,7.12,null,"Can the 3% to 5% defect rate be reduced?"]
[1,112.1,4.3978158479833718E-2,4.93]
[1,86.32,4.0461547857198944E-2,3.49]
[3,104.79,3.7231406323893185E-2,3.9]
[3,35.03,4.0967616308831743E-2,1.44]
[3,89.68,3.9302599801291652E-2,3.52]
[2,139.58000000000001,4.8355352926726755E-2,6.75]
[2,36.97,4.2633351076701437E-2,1.58]
[3,144.19,3.0533806082007349E-2,4.4000000000000004]
[2,32.119999999999997,4.5801232722466098E-2,1.47]
[3,114.35,4.8540005667352643E-2,5.55]
[3,94.38,3.2043834499270341E-2,3.02]
[2,119.39,4.6618062747112748E-2,5.57]
[1,179.81,3.4341974210819283E-2,6.18]
[1,200.68,3.9886699830095747E-2,8]
[3,156.16999999999999,3.7531308767697766E-2,5.86]
[3,108.88,4.040688399282278E-2,4.4000000000000004]
[2,67.27,4.3092198384669711E-2,2.9]
[3,80.02,3.3882830468998773E-2,2.71]
[1,95.28,4.4568410075450593E-2,4.25]
[2,72.16,3.5295317868824283E-2,2.5499999999999998]
[1,131.22999999999999,3.9618118733561122E-2,5.2]
[3,124.93,4.1619721501762755E-2,5.2]
[3,165.91,4.4570209277741052E-2,7.39]
[1,85.38,4.2129636150271939E-2,3.6]
[2,49.37,4.9355325873310957E-2,2.44]
[1,54.46,4.0321589840184094E-2,2.2000000000000002]
[3,90.61,4.0149840263031339E-2,3.64]
[1,56.59,3.0584460287111537E-2,1.73]
[1,60.47,4.6804868311288939E-2,2.83]
[1,78.2,4.879377994413503E-2,3.82]
[1,172.82,3.8943236045938509E-2,6.73]
[3,188.06,3.8954130660704064E-2,7.33]
[1,185.89,4.6806758506976742E-2,8.6999999999999993]
[1,110.96,3.2616740322881657E-2,3.62]
[3,32.57,4.9767246300969514E-2,1.62]
[1,103.18,4.1462621773437097E-2,4.28]
[1,165.66,4.1637619734557492E-2,6.9]
[2,177.87,3.7269176385281426E-2,6.63]
[3,165.99,4.2109958342297651E-2,6.99]
[3,122.16,4.4417881416145756E-2,5.43]
[3,177.36,3.978570644006537E-2,7.06]
[1,92.16,4.253485892462603E-2,3.92]
[2,137.07,4.1320239737287288E-2,5.66]
[3,82.63,4.1743548603786741E-2,3.45]
[2,93.04,3.8352945245653636E-2,3.57]
[3,82.21,3.1857266157111166E-2,2.62]
[1,30.36,3.937856711215084E-2,1.2]
[1,70.489999999999995,4.4719422136530462E-2,3.15]
[2,151.32,3.7607757871274371E-2,5.69]
[1,156.22,4.9586458345597328E-2,7.75]
[{"$f":"RANDBETWEEN(H$11,H$13)","v":3},{"$f":"RANDBETWEEN(G$4,H$4)+ROUND(RAND(),2)","v":57.83},{"$f":"G$5+RAND()*(H$5-G$5)","v":4.1202383285883305E-2},{"$f":"ROUND(B68*C68,2)","v":2.38}]
[2,86.13,3.1258311491348979E-2,2.69]
[3,83.01,3.6303261635687867E-2,3.01]
[2,184.31,3.4874098031262922E-2,6.43]
[1,179.15,4.603614965736133E-2,8.25]
[1,183.23,4.0489654306564427E-2,7.42]
[2,160.27000000000001,3.0101237563177976E-2,4.82]
[1,78.08,3.5127952666338683E-2,2.74]
[2,128.54,4.092018083651798E-2,5.26]
[1,183.31,3.5828065468222176E-2,6.57]
[1,173.31,3.9875380879987626E-2,6.91]
[3,186.32,3.1935463862160701E-2,5.95]
[2,55.83,4.6925879106557586E-2,2.62]
[3,98.88,3.311587868505373E-2,3.27]
[2,34.840000000000003,4.2843957155499129E-2,1.49]
[1,90.48,4.263570922338495E-2,3.86]
[2,144.08000000000001,3.6914308231146775E-2,5.32]
[1,53.13,3.4194298923256282E-2,1.82]
[3,196.23,3.6640944487443747E-2,7.19]
[3,135.13,4.2896911537348328E-2,5.8]
[1,27.36,4.8855355034906567E-2,1.34]
[1,166.81,4.6390563943696089E-2,7.74]
[2,200.58,4.6646884325136265E-2,9.36]
[3,79.7,4.6204721282911254E-2,3.68]
[3,151.71,3.6282828226734037E-2,5.5]
[3,41.5,3.0854510561570958E-2,1.28]
[2,70.760000000000005,3.838176424377529E-2,2.72]
[1,77.72,3.6879847614910519E-2,2.87]
[3,77.12,4.4251174888661024E-2,3.41]
[3,28.32,4.1348843514825942E-2,1.17]
[2,38.89,4.2784547863327221E-2,1.66]
[1,77.14,4.8910572784402875E-2,3.77]
[2,25.01,4.9778379303184635E-2,1.24]
[2,139.25,3.9949128583047659E-2,5.56]
[2,103.8,4.9705792723637773E-2,5.16]

{"sheet":"P149","index":35,"n_rows":110,"n_cols":5,"rows_kept":110,"cut":false,"hidden":false,"merged":[[1,2,1,3]]}
["Ski Bindings Labor Cost Analysis",null,null,null,"Quality Inspection Wage"]
[null,null,"Time in Minutes",null,38]
["item#","Type","Pressure-Test","Temperature-Test","Quality Inspection Cost"]
[1635,2,1.4,0.9,{"$f":"SUM(C4:D4)/60*E$2","v":1.4566666666666666}]
[1636,5,0.6,1.5,{"$f":"SUM(C5:D5)/60*E$2","v":1.33}]
[1637,1,1,2.9,2.4700000000000002]
[1638,5,2,1.1499999999999999,1.9949999999999999]
[1639,4,1.4,2.9,2.7233333333333336]
[1640,1,1.5,0.35,1.1716666666666666]
[1641,2,1.4,1.35,1.7416666666666665]
[1642,1,2.1,2,2.5966666666666667]
[1643,4,1,0.1,0.69666666666666666]
[1644,4,2.4,1.1499999999999999,2.2483333333333335]
[1645,5,1.9,3.5,3.4200000000000004]
[1646,4,1.4,2.15,2.2483333333333335]
[1647,2,2.4,2.65,3.1983333333333333]
[1648,3,1,1,1.2666666666666666]
[1649,2,2.6,1.1000000000000001,2.3433333333333333]
[1650,2,3.5,2.65,3.8950000000000005]
[1651,1,2,0.5,1.5833333333333333]
[1652,2,0.6,3.4,2.5333333333333332]
[1653,4,1.9,2.65,2.8816666666666668]
[1654,1,1,2.65,2.3116666666666665]
[1655,1,1.6,0.5,1.33]
[1656,5,0.6,0.75,0.85500000000000009]
[1657,5,0.6,3.35,2.5016666666666669]
[1658,2,0.6,1.1000000000000001,1.0766666666666667]
[1659,3,1.4,2.5,2.4700000000000002]
[1660,4,1,2.85,2.438333333333333]
[1661,5,1.6,2.6,2.66]
[1662,5,1.1000000000000001,2.65,2.375]
[1663,1,1.5,1,1.5833333333333333]
[1664,3,0.6,0.85,0.91833333333333333]
[1665,5,1.5,0.1,1.0133333333333334]
[1666,4,1.4,0.85,1.425]
[1667,2,2.9,1.35,2.6916666666666664]
[1668,3,0.6,0.9,0.95000000000000007]
[1669,2,2,0.85,1.8049999999999999]
[1670,2,1,2.9,2.4700000000000002]
[1671,4,1.5,2.15,2.3116666666666665]
[1672,5,1.6,2,2.2800000000000002]
[1673,2,1.9,3.9,3.6733333333333333]
[1674,2,2.9,1.25,2.6283333333333334]
[1675,2,0.6,1.35,1.2350000000000001]
[1676,3,3,2.35,3.3883333333333332]
[1677,3,1.5,2,2.2166666666666668]
[1678,3,1.5,0.85,1.4883333333333335]
[1679,4,1.9,3,3.1033333333333339]
[1680,1,2.5,0.5,1.9000000000000001]
[1681,3,0.6,0.35,0.60166666666666657]
[1682,4,1.4,3.15,2.8816666666666668]
[1683,4,1.9,0.6,1.5833333333333333]
[1684,1,1.6,1.1499999999999999,1.7416666666666665]
[1685,1,3.9,0.1,2.5333333333333332]
[1686,3,2.4,2.5,3.1033333333333339]
[1687,3,1,0.9,1.2033333333333331]
[1688,2,1.4,1.1000000000000001,1.5833333333333333]
[1689,1,1.4,1.1499999999999999,1.6149999999999998]
[1690,2,1.4,2.25,2.3116666666666665]
[1691,5,1.5,3.15,2.9449999999999998]
[1692,1,2.9,3.1,3.8000000000000003]
[1693,4,0.6,0.6,0.76]
[1694,3,1,2.5,2.2166666666666668]
[1695,5,1,3.1,2.5966666666666667]
[1696,3,4.4000000000000004,2.4,4.3066666666666666]
[1697,1,1.9,1.35,2.0583333333333336]
[1698,2,1,0.9,1.2033333333333331]
[1699,2,2.4,0.1,1.5833333333333333]
[1700,4,1.5,2.65,{"$f":"SUM(C69:D69)/60*E$2","v":2.6283333333333334}]
[1701,1,1.4,0.1,0.95000000000000007]
[1702,2,2.6,0.9,2.2166666666666668]
[1703,4,2.4,2.25,2.9449999999999998]
[1704,5,1,2.1,1.9633333333333334]
[1705,1,1.4,1.35,1.7416666666666665]
[1706,3,1.4,1.65,1.9316666666666664]
[1707,5,1.4,1.1000000000000001,1.5833333333333333]
[1708,5,1.4,0.9,1.4566666666666666]
[1709,4,2.4,0.9,2.09]
[1710,3,1.4,3.15,2.8816666666666668]
[1711,1,0.6,0.5,0.69666666666666666]
[1712,3,1,0.5,0.95000000000000007]
[1713,1,1,0.5,0.95000000000000007]
[1714,3,1.1000000000000001,1.1499999999999999,1.425]
[1715,1,0.6,1.6,1.3933333333333333]
[1716,4,1.4,2.15,2.2483333333333335]
[1717,2,2.4,1.1499999999999999,2.2483333333333335]
[1718,4,3.5,0.85,2.7549999999999999]
[1719,2,1.9,3.4,3.3566666666666665]
[1720,2,2.9,1.35,2.6916666666666664]
[1721,5,2.5,1.4,2.4700000000000002]
[1722,4,1,1.4,1.52]
[1723,4,0.6,1.6,1.3933333333333333]
[1724,4,1.4,1.4,1.7733333333333332]
[1725,5,1.1000000000000001,1.85,1.8683333333333334]
[1726,2,2.1,0.1,1.3933333333333333]
[1727,3,1.1000000000000001,0.1,0.76000000000000012]
[1728,3,1.1000000000000001,2.75,2.438333333333333]
[1729,3,0.6,2.5,1.9633333333333334]
[1730,2,1,0.6,1.0133333333333334]
[1731,3,0.6,2.1,{"$f":"SUM(C100:D100)/60*E$2","v":1.7100000000000002}]
[1732,1,3.1,1.6,{"$f":"SUM(C101:D101)/60*E$2","v":2.976666666666667}]
[1733,4,1.4,0.9,{"$f":"SUM(C102:D102)/60*E$2","v":1.4566666666666666}]
[1734,5,1.1000000000000001,0.5,{"$f":"SUM(C103:D103)/60*E$2","v":1.0133333333333334}]
[]
[]
[]
["Total",null,{"$f":"SUM(C4:C103)","v":159.10000000000008},{"$f":"SUM(D4:D103)","v":160.44999999999996},{"$f":"SUM(E4:E103)","v":202.38166666666669}]
["Average",null,{"$f":"AVERAGE(C4:C103)","v":1.5910000000000009},{"$f":"AVERAGE(D4:D103)","v":1.6044999999999996},{"$f":"AVERAGE(E4:E103)","v":2.0238166666666668}]
["Median",null,{"$f":"MEDIAN(C4:C103)","v":1.4},1.35,1.9791666666666665]
["Standard Deviation",null,{"$f":"STDEV(C4:C103)","v":0.8025332366697312},{"$f":"STDEV(D4:D103)","v":0.98616938225897655},{"$f":"STDEV(E4:E103)","v":0.80738358571953805}]

{"sheet":"P150","index":36,"n_rows":11,"n_cols":5,"rows_kept":11,"cut":false,"hidden":false,"merged":[]}
["Binding Type Average Analysis"]
[]
["Type","Count",{"$f":"\"Average \"&'P149'!C3","v":"Average Pressure-Test"},{"$f":"\"Average \"&'P149'!D3","v":"Average Temperature-Test"},{"$f":"\"Average \"&'P149'!E3","v":"Average Quality Inspection Cost"}]
[1,{"$f":"COUNTIF('P149'!B$4:B$103,A4)","v":19},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A4,'P149'!C$4:C$103)","v":1.7368421052631575},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A4,'P149'!D$4:D$103)","v":1.205263157894737},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A4,'P149'!E$4:E$103)","v":1.8633333333333331}]
[2,{"$f":"COUNTIF('P149'!B$4:B$103,A5)","v":23},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A5,'P149'!C$4:C$103)","v":1.8652173913043475},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A5,'P149'!D$4:D$103)","v":1.5913043478260871},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A5,'P149'!E$4:E$103)","v":2.189130434782609}]
[3,{"$f":"COUNTIF('P149'!B$4:B$103,A6)","v":20},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A6,'P149'!C$4:C$103)","v":1.3650000000000002},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A6,'P149'!D$4:D$103)","v":1.6499999999999997},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A6,'P149'!E$4:E$103)","v":1.9095}]
[4,{"$f":"COUNTIF('P149'!B$4:B$103,A7)","v":21},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A7,'P149'!C$4:C$103)","v":1.5904761904761904},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A7,'P149'!D$4:D$103)","v":1.7261904761904763},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A7,'P149'!E$4:E$103)","v":2.1005555555555557}]
[5,{"$f":"COUNTIF('P149'!B$4:B$103,A8)","v":17},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A8,'P149'!C$4:C$103)","v":1.3235294117647058},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A8,'P149'!D$4:D$103)","v":1.8647058823529414},{"$f":"AVERAGEIF('P149'!$B$4:$B$103,$A8,'P149'!E$4:E$103)","v":2.0192156862745101}]
[]
["Total counted",{"$f":"SUM(B4:B8)","v":100}]
["Total Costs for all inspections",{"$f":"SUM('P149'!E4:E103)","v":202.38166666666669}]

{"sheet":"P150-151","index":37,"n_rows":102,"n_cols":8,"rows_kept":102,"cut":false,"hidden":false,"merged":[]}
["Ski Return Cost Simulation",null,null,null,null,"Costs of not inspecting"]
["Style","Return Cost (between 20 and 75)","Probability of Failure (between 1% and 3%","Probable Cost",null,"Handling and returning the defective binding"]
[{"$f":"RANDBETWEEN(G$11,G$15)","v":3},{"$f":"RANDBETWEEN(G$4,H$4)+ROUND(RAND(),2)","v":59.56},{"$f":"G$5+RAND()*(H$5-G$5)","v":2.0247748914920097E-2},{"$f":"ROUND(B3*C3,2)","v":1.21},null,"Getting new binding to customer"]
[3,67.459999999999994,{"$f":"G$5+RAND()*(H$5-G$5)","v":2.2575832570143999E-2},{"$f":"ROUND(B4*C4,2)","v":1.52},null,"Costs vary between",20,75]
[4,29.29,1.7633895110787494E-2,0.52,null,"binding Failure rate varies between",0.01,0.03]
[4,64.53,1.9323390286554484E-2,1.25,null,"Number of bindings",100]
[5,24.13,1.4938583049150907E-2,0.36,null,"Estimation of Cost of not inspecting =",{"$f":"AVERAGE(G4:H4)*AVERAGE(G5:H5)*G6","v":95}]
[2,58.17,1.8742989397929562E-2,1.0900000000000001,null,"Time Data for Quality Control Testing - Per binding Total",{"$f":"'P149'!E107","v":202.38166666666669}]
[5,55.52,2.4256686345707643E-2,1.35]
[4,56.25,1.6054636035459424E-2,0.9,null,"Simulated probable Costs for by Ski Type","Style"]
[1,65.150000000000006,2.6067564345868002E-2,1.7,null,{"$f":"SUMIF(A$3:A$102,G11,D$3:D$102)","v":23.299999999999997},1]
[3,56.85,2.8722134320204984E-2,1.63,null,{"$f":"SUMIF(A$3:A$102,G12,D$3:D$102)","v":14.440000000000001},2]
[5,42.67,1.2702168483916285E-2,0.54,null,{"$f":"SUMIF(A$3:A$102,G13,D$3:D$102)","v":23.94},3]
[3,67.06,2.564745999406403E-2,1.72,null,{"$f":"SUMIF(A$3:A$102,G14,D$3:D$102)","v":23.310000000000002},4]
[5,59.05,1.7598304913964274E-2,1.04,null,{"$f":"SUMIF(A$3:A$102,G15,D$3:D$102)","v":18.47},5]
[3,74.11,2.4978373092434648E-2,1.85]
[4,71.2,1.8388309833386723E-2,1.31,null,{"$f":"SUM(F11:F15)","v":103.46},"Simulated"]
[3,63.82,2.9442036676394494E-2,1.88,null,{"$f":"'P149'!E107","v":202.38166666666669},"Actual from batch"]
[4,67.58,2.568936011928754E-2,1.74]
[1,72.14,2.066262833427733E-2,1.49,null,"It seems because the defect rate is lower than the 3% to 5% we saw before, not inspecting costs less than inspecting"]
[1,75.45,1.5255806134201241E-2,1.1499999999999999,null,"Is it better to not inspect?"]
[4,45.99,2.2736487679251245E-2,1.05,null,"How will customer satisfcatiob change?"]
[3,74.22,1.2518398027179547E-2,0.93,null,"What are the liabilities?"]
[4,58.68,1.0169993712579775E-2,0.6,null,"Will people get hurt?"]
[1,57.43,1.9629731198338479E-2,1.1299999999999999,null,"If we change the hourly inspection rate to $30, not inspecting still is less 95 ave , 159.78."]
[1,66.97,2.5718302318098976E-2,1.72,null,"For total inspection to be $100, the hourly rate would have to be $18.78"]
[3,30.93,2.5805283524710322E-2,0.8]
[1,66.55,1.6508667440938856E-2,1.1000000000000001]
[3,45.18,1.7702945355683404E-2,0.8]
[3,40.549999999999997,2.1697494974794045E-2,0.88]
[5,68.819999999999993,2.1492162221209657E-2,1.48]
[1,62.08,2.5997939216231156E-2,1.61]
[4,54.56,2.3143652170443722E-2,1.26]
[2,35.49,1.8736871687111765E-2,0.66]
[2,39.31,1.7187804556265777E-2,0.68]
[4,62.16,1.0832911134584294E-2,0.67]
[4,50.71,1.0804012371673935E-2,0.55000000000000004]
[4,37.97,2.0252760604086165E-2,0.77]
[2,43.61,1.1777263778656684E-2,0.51]
[2,75.64,1.0986688215823897E-2,0.83]
[5,37.1,1.0683862989752005E-2,0.4]
[5,36.72,2.3725655306931073E-2,0.87]
[1,63.51,2.5045175764556726E-2,1.59]
[3,50.62,1.6593550914997621E-2,0.84]
[5,51.11,1.047315878736713E-2,0.54]
[3,33.22,1.7550203775766507E-2,0.57999999999999996]
[4,21.82,2.3271309755801085E-2,0.51]
[3,56.02,1.9508786807534866E-2,1.0900000000000001]
[5,71.31,2.8191740150941315E-2,2.0099999999999998]
[3,73.27,2.4206926800213108E-2,1.77]
[4,30.89,2.5352957119792463E-2,0.78]
[3,57.64,2.2187000616396391E-2,1.28]
[5,27.12,2.850920030520878E-2,0.77]
[5,69.13,1.4536152905054785E-2,1]
[1,54.71,1.9554372861107915E-2,1.07]
[4,38.96,2.7248987717355948E-2,1.06]
[1,61.49,2.9479079327411957E-2,1.81]
[5,64.489999999999995,1.9196168861474551E-2,1.24]
[2,56.86,2.039427467819558E-2,1.1599999999999999]
[4,23.02,2.7587270831794082E-2,0.64]
[4,33.5,2.1226912935336469E-2,0.71]
[1,52.57,1.6483219630108598E-2,0.87]
[1,21.71,1.6517479693107101E-2,0.36]
[4,57.07,1.7880807138974743E-2,1.02]
[4,45.43,2.099751090516247E-2,0.95]
[2,38.44,2.1085873335655446E-2,0.81]
[{"$f":"RANDBETWEEN(G$11,G$15)","v":5},{"$f":"RANDBETWEEN(G$4,H$4)+ROUND(RAND(),2)","v":43.85},1.7984228864054687E-2,0.79]
[3,55.78,{"$f":"G$5+RAND()*(H$5-G$5)","v":1.6616425093517413E-2},{"$f":"ROUND(B68*C68,2)","v":0.93}]
[5,28.11,1.8854088992558873E-2,0.53]
[4,51.3,2.7012163236979102E-2,1.39]
[4,40.5,1.6284850169008179E-2,0.66]
[1,69.42,2.7307306394833954E-2,1.9]
[1,49.93,2.2077190518015911E-2,1.1000000000000001]
[5,66.790000000000006,2.1826217575598029E-2,1.46]
[2,68.02,1.386056621702509E-2,0.94]
[1,52.02,2.8737442493480231E-2,1.49]
[4,63.18,1.2480879109635853E-2,0.79]
[5,45.5,2.7942779332067222E-2,1.27]
[4,54.26,1.6442276434384711E-2,0.89]
[5,28.55,2.7008512008311211E-2,0.77]
[3,35.520000000000003,1.5517307681390839E-2,0.55000000000000004]
[3,45.93,2.820844701511209E-2,1.3]
[2,63.72,2.6076500600035413E-2,1.66]
[4,31.34,1.0139559093602877E-2,0.32]
[4,32.090000000000003,2.5163144075062493E-2,0.81]
[3,22.47,1.5147636148611747E-2,0.34]
[1,49.15,2.7339219647040537E-2,1.34]
[3,44.56,1.1566115990943012E-2,0.52]
[2,72.94,1.4432097270530892E-2,1.05]
[2,72.900000000000006,1.0253517992976798E-2,0.75]
[4,44.97,1.3395627948693579E-2,0.6]
[5,62.59,1.2078350503504965E-2,0.76]
[1,71.97,2.603731209556473E-2,1.87]
[3,66.73,2.282696856835921E-2,1.52]
[2,52.22,1.4568171564988823E-2,0.76]
[4,47.06,2.3394256415072937E-2,1.1000000000000001]
[4,20.07,2.3061693756385379E-2,0.46]
[2,36.76,2.4576422158245598E-2,0.9]
[2,54.79,1.8468211807187794E-2,1.01]
[2,59.59,1.2313994080235684E-2,0.73]
[2,37.520000000000003,2.3924467412199509E-2,0.9]
[5,51.82,2.4925800524244229E-2,1.29]

{"sheet":"P153-155","index":38,"n_rows":42,"n_cols":10,"rows_kept":42,"cut":false,"hidden":false,"merged":[]}
["Flavor","# Pints Sold Current Quarter","# Gallons Sold Current Quarter","# Tubs Used Current Quarter","Total Sold Current Quarter  in Gallons","Current Flavor Gallons as a % of Total","Total Sold Same Quarter Last Year in Gallons","Historical Flavor Gallons as a % of Total","Total Sold Amount Change","Total Sold % Change"]
["Vanilla",154957,6832,1013.37,{"$f":"B2/A$40+C2+ROUNDDOWN(D2*C$41,0)","v":36334.625},{"$f":"E2/E$25","v":7.3862179597128319E-2},55343,{"$f":"G2/G$25","v":0.12743064110209787},{"$f":"IF(AND(E2=\"\",G2=\"\"),\"\",E2-G2)","v":-19008.375},{"$f":"IF(AND(OR(G2=\"\",G2=0),OR(E2=\"\",E2=0)),\"\",IF(AND(OR(G2=0,G2=\"\"),E2<>0),1,I2/G2))","v":-0.34346484650271941}]
["Chocolate",215191,17424,5954.88,103870.875,0.21115201338009862,76855,0.17696333631898761,27015.875,0.35151746795914385]
["Strawberry",27503,3365,1780.98,24611.875,5.0031801111806509E-2,22436,5.1660261709099028E-2,2175.875,9.6981413799251209E-2]
["Maple Walnut",57513,2701,571.6,15606.125,3.1724626511632756E-2,11432,2.6322878938243009E-2,4174.125,0.36512639958012594]
["Praline",76236,2692,730.46,19525.5,3.9692056481213968E-2,14609,3.3638115676066491E-2,4916.5,0.33653911972072009]
["Butter Pecan",38361,2705,136.44999999999999,8864.125,1.8019274802516746E-2,16253,3.742352618817911E-2,-7388.875,-0.45461607087922229]
["Chocolate Chip",99103,5309,1834.26,36038.875,7.3260969604845461E-2,35395,8.1499151506220363E-2,643.875,1.8191128690493007E-2]
["Mint Chocolate Chip",91186,1469,333.97,16206.25,3.2944579670106978E-2,18935,4.3598995162319049E-2,-2728.75,-0.14411143385265382]
["Cookie Dough",91233,3516,956.68,24486.125,4.9776172518299931E-2,23443,5.3978940775824949E-2,1043.125,4.4496224885893443E-2]
["Rocky Road",46187,3889,824.78,17909.375,3.6406746257112051E-2,16496,3.7983048544896487E-2,1413.375,8.5679861784675071E-2]
["Fudge Swirl",51974,2857,1122.23,20575.75,4.1827038034536287E-2,18394,4.2353309586252788E-2,2181.75,0.11861204740676308]
["Peach",65808,1595,1175.1500000000001,21572,4.3852246672953198E-2,23504,5.4119397005288984E-2,-1932,-8.2198774676650779E-2]
["Pumpkin",0,0,0,0,0,0,0,{"$f":"IF(AND(E14=\"\",G14=\"\"),\"\",E14-G14)","v":0},{"$f":"IF(AND(OR(G14=\"\",G14=0),OR(E14=\"\",E14=0)),\"\",IF(AND(OR(G14=0,G14=\"\"),E14<>0),1,I14/G14))","v":""}]
["Marshmallow Fudge",8467,809,239.19,4258.375,8.6565599353762776E-3,5392,1.2415409660165001E-2,-1133.625,-0.21024202522255192]
["Coffee",228592,6485,2161.73,56676,0.11521277268849878,43235,9.9551230834056717E-2,13441,0.3108823869550133]
["Mocha Chip",130943,4985,168.85,23040.875,4.6838222420762125E-2,33235,7.652561944651036E-2,-10194.125,-0.30672859936813601]
["Raspberry",0,0,0,0,0,0,0,0,""]
["Watermelon",54154,3181,1395.27,23902.25,4.8589252875885204E-2,19342,4.4536137545792186E-2,4560.25,0.23576931030917175]
["Cinnamon Spice",0,0,0,0,0,0,0,0,""]
["Chocolate Fudge",47952,3381,170.56,11080,2.2523775873183823E-2,null,0,11080,{"$f":"IF(AND(OR(G21=\"\",G21=0),OR(E21=\"\",E21=0)),\"\",IF(AND(OR(G21=0,G21=\"\"),E21<>0),1,I21/G21))","v":1}]
["Cherry Vanilla",69125,3800,1492.56,27365.625,5.562971156404297E-2,null,0,27365.625,{"$f":"IF(AND(OR(G22=\"\",G22=0),OR(E22=\"\",E22=0)),\"\",IF(AND(OR(G22=0,G22=\"\"),E22<>0),1,I22/G22))","v":1}]
[]
[null,null,null,null,null,null,null,"% change"]
[null,null,null,"Total",{"$f":"SUM(E2:E22)","v":491924.625},null,{"$f":"SUM(G2:G22)","v":434299},{"$f":"E25/G25-1","v":0.13268652472144771}]
[null,null,null,"Mean",{"$f":"AVERAGE(E2:E22)","v":23424.982142857141},null,{"$f":"AVERAGE(G2:G22)","v":22857.842105263157}]
[null,null,null,"Median",{"$f":"MEDIAN(E2:E22)","v":20575.75},null,{"$f":"MEDIAN(G2:G22)","v":18935}]
[null,null,null,"Mode",{"$f":"MODE(E2:E22)","v":0},null,{"$f":"MODE(G2:G22)","v":0}]
[null,null,null,"Stdev",{"$f":"STDEV(E2:E22)","v":22879.870274547753},null,{"$f":"STDEV(G2:G22)","v":19514.77383438039}]
[null,null,null,"Skew",{"$f":"SKEW(E2:E22)","v":2.3527229922923656},null,{"$f":"SKEW(G2:G22)","v":1.3311218640578739}]
[]
["Assumptions/Inputs, Information, and Directions"]
["Compare quarterly ice cream sales volumes (gallons) from all regional locations for this quarter and same quarter last year"]
["Pints and gallons sold to public"]
["10 gallon tubs sold in store for cones and the like"]
["To eliminate price changes or promotions, volume is used for analysis instead of dollar value of flavors"]
["1 workbook for this quarter"]
["1 workbook for historical data"]
["New flavors this year at bottom"]
[8," =",1]
[1," =",10]
["When making calculations for Tubs, ROUNDDOWN to the nearest Tub."]

{"sheet":"P155","index":39,"n_rows":214,"n_cols":9,"rows_kept":214,"cut":false,"hidden":false,"merged":[]}
["Assumptions/Inputs, Information, and Directions",null,null,"Current Total",{"$f":"SUM(B14:B214)","v":1903250},null,null,"Amount Change","% Change"]
["Summarizes Sales in Dollars by Store",null,null,"Current Mean",{"$f":"AVERAGE(B14:B214)","v":9468.9054726368158},"Historical Mean",8817,{"$f":"E2-G2","v":651.90547263681583},{"$f":"H2/G2","v":7.3937333859228294E-2}]
["Compare summary to previous year",null,null,"Current Median",{"$f":"MEDIAN(B14:B214)","v":9250},"Historical Median",8000,{"$f":"E3-G3","v":1250},{"$f":"H3/G3","v":0.15625}]
["Numbers are rounded to the thousands position",null,null,"Current Mode",{"$f":"MODE(B14:B214)","v":5500},"Historical Mode",5500,{"$f":"E4-G4","v":0},{"$f":"H4/G4","v":0}]
["Compare sales by store with SUM, MEAN, MEDIAN, MODE, STDEV",null,null,"Current Stdev",{"$f":"STDEV(B14:B214)","v":5347.7767152359584},"Historical Standard Deviation",6920,{"$f":"E5-G5","v":-1572.2232847640416},{"$f":"H5/G5","v":-0.22719989664220255}]
["Historical Mean",8817,null,"Current Skew",{"$f":"SKEW(B14:B214)","v":2.1336410568205656E-2}]
["Historical Median",8000]
["Historical Mode",5500,null,"The Average Sales have jumped by 7.39% and the variation in sales per store has dropped. Average sales are up and this is good; matched with the reduction is sales variation per store (means less variation between sales at store or more consistent sales). In particular more consistent sales reduced future uncertainty and helps managers plan with more ease. For these reasons, things are better for this quarter as compared to the same quarter last year."]
["Historical Standard Deviation",6920]
[null,null,null,"Total Sales/Total Gallons = Ave. Sales/1 gal =",{"$f":"E1/'P153-155'!E25","v":3.8689870424762738}]
[]
[]
["Store#","Sales (Rounded to the Thousands Position"]
[101,2250]
[102,10500]
[103,8500]
[104,12250]
[105,1500]
[106,2000]
[107,11000]
[108,17750]
[109,5500]
[110,13250]
[111,14500]
[112,11500]
[113,8250]
[114,12000]
[115,16500]
[116,17000]
[117,1750]
[118,8000]
[119,9500]
[120,2000]
[121,750]
[122,18500]
[123,14750]
[124,2250]
[125,16500]
[126,15000]
[127,1750]
[128,2500]
[129,5750]
[130,7500]
[131,4250]
[132,7000]
[133,6000]
[134,13500]
[135,8750]
[136,10500]
[137,16750]
[138,6500]
[139,4000]
[140,17500]
[141,12750]
[142,6750]
[143,9000]
[144,12500]
[145,2250]
[146,7000]
[147,14750]
[148,10250]
[149,7250]
[150,11250]
[151,7750]
[152,14750]
[153,1750]
[154,5500]
[155,17250]
[156,6500]
[157,5000]
[158,12250]
[159,16500]
[160,4250]
[161,16000]
[162,3500]
[163,1000]
[164,14000]
[165,15250]
[166,5750]
[167,5500]
[168,10750]
[169,16000]
[170,2250]
[171,15250]
[172,16250]
[173,3500]
[174,13750]
[175,9000]
[176,4000]
[177,17250]
[178,10750]
[179,17750]
[180,7250]
[181,16000]
[182,15500]
[183,12250]
[184,18250]
[185,11000]
[186,8000]
[187,18250]
[188,11000]
[189,1500]
[190,8000]
[191,0]
[192,12750]
[193,10500]
[194,15750]
[195,12500]
[196,9250]
[197,18250]
[198,17750]
[199,18250]
[200,4750]
[201,11750]
[202,9250]
[203,5500]
[204,17250]
[205,8250]
[206,5500]
[207,1250]
[208,9500]
[209,11750]
[210,2500]
[211,18000]
[212,9500]
[213,9250]
[214,1500]
[215,5000]
[216,12250]
[217,14500]
[218,15000]
[219,13250]
[220,16250]
[221,14500]
[222,17250]
[223,15250]
[224,18000]
[225,6250]
[226,3750]
[227,9250]
[228,14750]
[229,750]
[230,3000]
[231,13750]
[232,250]
[233,18250]
[234,14250]
[235,14750]
[236,15000]
[237,8500]
[238,3500]
[239,6750]
[240,3750]
[241,1250]
[242,2500]
[243,10500]
[244,3750]
[245,5750]
[246,15250]
[247,9250]
[248,18000]
[249,4000]
[250,8250]
[251,7750]
[252,10500]
[253,6250]
[254,9500]
[255,1500]
[256,3500]
[257,10500]
[258,9000]
[259,13000]
[260,9500]
[261,16000]
[262,3250]
[263,6500]
[264,4250]
[265,8000]
[266,10000]
[267,12750]
[268,10000]
[269,14000]
[270,9750]
[271,7500]
[272,2000]
[273,9750]
[274,16500]
[275,17000]
[276,1750]
[277,1250]
[278,1250]
[279,4500]
[280,13250]
[281,8000]
[282,18000]
[283,2250]
[284,1500]
[285,15750]
[286,13750]
[287,10250]
[288,3750]
[289,4000]
[290,2500]
[291,8250]
[292,16750]
[293,8750]
[294,6000]
[295,11250]
[296,5500]
[297,17250]
[298,2500]
[299,8500]
[300,5500]
[301,11000]

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["Assumptions/Inputs, Information, Directions"]
["Open resturant that specializes in fine cuisine and specialty deserts"]
["We must decide where to located: Location, Location, Location!"]
["Location 1:","Near large retail area"]
[null,"Fringe of affluent suburbs"]
["Location 2:","Downtaown district"]
["Highered Local Market Resecrh Firm to find out:","Demogarphics"]
[null,"Specific dining habits"]
[]
["Age Category","Income"]
["18-21",5000]
["22-25",10000]
["26-30",20000]
["30-35",30000]
["over 35",40000]
[null,50000]
[null,75000]
[null,100000]

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[101,"30-35",100000,5,45,15,13]
[102,"26-30",75000,3,57,24,1]
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[104,"30-35",100000,12,23,3,65]
[105,"26-30",50000,8,34,19,7]
[106,"30-35",20000,1,67,8,38]
[107,"30-35",100000,18,8,12,20]
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[109,"30-35",100000,4,50,20,4]
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[111,"18-21",30000,0,74,6,49]
[112,"22-25",30000,4,50,12,20]
[113,"18-21",30000,0,74,3,65]
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[128,"22-25",5000,14,15,6,49]
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[130,"18-21",10000,0,74,2,79]
[131,"18-21",10000,0,74,7,42]
[132,"26-30",100000,11,26,6,49]
[133,"22-25",10000,3,57,5,55]
[134,"22-25",50000,13,19,8,38]
[135,"22-25",20000,6,42,3,65]
[136,"26-30",20000,6,42,11,26]
[137,"18-21",10000,0,74,2,79]
[138,"30-35",75000,1,67,3,65]
[139,"22-25",30000,20,3,9,32]
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[145,"18-21",20000,0,74,18,8]
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[148,"22-25",5000,15,14,5,55]
[149,"22-25",50000,14,15,14,17]
[150,"22-25",40000,20,3,23,2]
[151,"22-25",50000,13,19,9,32]
[152,"22-25",5000,3,57,4,59]
[153,"18-21",40000,0,74,9,32]
[154,"30-35",100000,3,57,16,11]
[155,"26-30",50000,20,3,12,20]
[156,"18-21",30000,0,74,2,79]
[157,"18-21",30000,0,74,7,42]
[158,"30-35",100000,7,38,17,9]
[159,"26-30",30000,5,45,11,26]
[160,"18-21",10000,0,74,1,93]
[161,"26-30",75000,18,8,0,103]
[162,"over 35",100000,8,34,10,29]
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[165,"22-25",100000,7,38,12,20]
[166,"30-35",5000,2,64,2,79]
[167,"over 35",50000,6,42,7,42]
[168,"26-30",20000,1,67,2,79]
[169,"26-30",50000,7,38,3,65]
[170,"26-30",30000,3,57,8,38]
[171,"18-21",20000,0,74,3,65]
[172,"30-35",40000,10,29,17,9]
[173,"26-30",30000,3,57,4,59]
[174,"18-21",5000,0,74,12,20]
[175,"over 35",10000,20,3,2,79]
[176,"26-30",20000,25,1,1,93]
[177,"18-21",5000,0,74,1,93]
[178,"22-25",50000,5,45,8,38]
[179,"over 35",20000,1,67,7,42]
[180,"18-21",30000,0,74,9,32]
[181,"30-35",100000,14,15,15,13]
[182,"26-30",5000,2,64,2,79]
[183,"30-35",100000,9,32,16,11]
[184,"26-30",20000,17,11,2,79]
[185,"18-21",40000,0,74,1,93]
[186,"18-21",30000,0,74,3,65]
[187,"18-21",30000,0,74,6,49]
[188,"26-30",5000,18,8,1,93]
[189,"over 35",10000,8,34,3,65]
[190,"22-25",75000,13,19,6,49]
[191,"18-21",10000,0,74,4,59]
[192,"26-30",20000,11,26,2,79]
[193,"26-30",40000,22,2,15,13]
[194,"18-21",10000,0,74,5,55]
[195,"22-25",75000,17,11,1,93]
[196,"18-21",30000,0,74,3,65]
[197,"22-25",75000,12,23,4,59]
[198,"22-25",100000,16,13,21,3]
[199,"18-21",5000,0,74,9,32]
[200,"18-21",40000,0,74,9,32]
[201,"over 35",100000,7,38,2,79]
[202,"22-25",5000,4,50,1,93]
[203,"26-30",10000,5,45,0,103]
[204,"26-30",75000,4,50,7,42]
[205,"26-30",30000,4,50,2,79]
[206,"over 35",100000,0,74,1,93]

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[130,"18-21",10000,0,95,0,106]
[131,"18-21",10000,8,41,12,45]
[132,"26-30",40000,0,95,7,69]
[133,"22-25",30000,16,13,23,11]
[134,"22-25",30000,3,70,28,1]
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[146,"18-21",10000,18,8,15,34]
[147,"26-30",5000,1,87,17,24]
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[149,"22-25",100000,3,70,18,23]
[150,"22-25",30000,4,62,14,38]
[151,"22-25",30000,11,26,27,2]
[152,"22-25",20000,2,75,11,51]
[153,"18-21",30000,19,5,19,20]
[154,"over 35",20000,18,8,4,82]
[155,"26-30",30000,19,5,10,54]
[156,"18-21",10000,5,57,19,20]
[157,"18-21",40000,11,26,4,82]
[158,"30-35",100000,2,75,3,88]
[159,"26-30",20000,0,95,12,45]
[160,"18-21",20000,13,22,6,74]
[161,"26-30",40000,4,62,2,94]
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[165,"22-25",75000,9,34,10,54]
[166,"30-35",100000,7,45,4,82]
[167,"over 35",100000,14,19,13,42]
[168,"over 35",20000,0,95,2,94]
[169,"over 35",50000,1,87,12,45]
[170,"26-30",100000,2,75,25,5]
[171,"18-21",20000,23,1,14,38]
[172,"30-35",75000,17,10,1,101]
[173,"26-30",10000,4,62,8,63]
[174,"18-21",5000,16,13,20,16]
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[176,"26-30",30000,8,41,3,88]
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[178,"22-25",5000,0,95,5,78]
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[181,"30-35",40000,1,87,12,45]
[182,"26-30",30000,17,10,11,51]
[183,"30-35",100000,2,75,17,24]
[184,"30-35",30000,16,13,20,16]
[185,"18-21",5000,9,34,0,106]
[186,"18-21",20000,1,87,7,69]
[187,"18-21",30000,4,62,22,12]
[188,"26-30",100000,1,87,26,4]
[189,"over 35",100000,20,3,9,58]
[190,"22-25",20000,5,57,16,27]
[191,"18-21",30000,2,75,24,7]
[192,"26-30",100000,13,22,24,7]
[193,"26-30",20000,0,95,9,58]
[194,"18-21",10000,6,51,9,58]
[195,"22-25",5000,17,10,20,16]
[196,"18-21",10000,0,95,22,12]
[197,"22-25",20000,3,70,13,42]
[198,"22-25",100000,0,95,5,78]
[199,"18-21",10000,6,51,6,74]
[200,"18-21",10000,10,31,3,88]
[201,"over 35",40000,15,17,2,94]
[202,"22-25",75000,2,75,7,69]
[203,"30-35",30000,6,51,16,27]
[204,"26-30",5000,3,70,11,51]
[205,"30-35",100000,1,87,8,63]
[206,"over 35",10000,11,26,7,69]
[]
[]
["Assumption for Condistions Formatting"]
[null,null,{"$f":"'P155(2)'!B17","v":75000},{"$f":"RIGHT('P156(2)'!A4,1)+0","v":5}]

{"sheet":"P156(1)","index":43,"n_rows":25,"n_cols":8,"rows_kept":25,"cut":false,"hidden":false,"merged":[[6,4,23,7]]}
["Mean and Standard Deviation Analysis"]
[{"$f":"'P155(3)'!A$1&\" Mean for \"&'P155(3)'!D$2","v":"SiteX Mean for #Desserts Out per Month"},{"$f":"'P155(4)'!A$1&\" Mean for \"&'P155(4)'!D$2","v":"SiteY Mean for #Desserts Out per Month"},"Difference (Y - X)","% Difference",{"$f":"'P155(3)'!A$1&\" Mean for \"&'P155(3)'!F$2","v":"SiteX Mean for # Meals out per Month"},{"$f":"'P155(4)'!A$1&\" Mean for \"&'P155(4)'!F$2","v":"SiteY Mean for # Meals out per Month"},"Difference (Y - X)","% Difference"]
[{"$f":"AVERAGE(xd)","v":{"$error":"#NAME?"}},{"$f":"AVERAGE(yd)","v":{"$error":"#NAME?"}},{"$f":"B3-A3","v":{"$error":"#NAME?"}},{"$f":"C3/A3","v":{"$error":"#NAME?"}},{"$f":"AVERAGE(xm)","v":{"$error":"#NAME?"}},{"$f":"AVERAGE(ym)","v":{"$error":"#NAME?"}},{"$f":"F3-E3","v":{"$error":"#NAME?"}},{"$f":"G3/E3","v":{"$error":"#NAME?"}}]
[{"$f":"'P155(3)'!A$1&\" Standard Deviation for \"&'P155(3)'!D$2","v":"SiteX Standard Deviation for #Desserts Out per Month"},{"$f":"'P155(4)'!A$1&\" Standard Deviation for \"&'P155(4)'!D$2","v":"SiteY Standard Deviation for #Desserts Out per Month"},"Difference (Y - X)","% Difference",{"$f":"'P155(3)'!A$1&\" Standard Deviation for \"&'P155(3)'!F$2","v":"SiteX Standard Deviation for # Meals out per Month"},{"$f":"'P155(4)'!A$1&\" Standard Deviation for \"&'P155(4)'!F$2","v":"SiteY Standard Deviation for # Meals out per Month"},"Difference (Y - X)","% Difference"]
[{"$f":"STDEV(xd)","v":{"$error":"#NAME?"}},{"$f":"STDEV(yd)","v":{"$error":"#NAME?"}},{"$f":"B5-A5","v":{"$error":"#NAME?"}},{"$f":"C5/A5","v":{"$error":"#NAME?"}},{"$f":"STDEV(xm)","v":{"$error":"#NAME?"}},{"$f":"STDEV(ym)","v":{"$error":"#NAME?"}},{"$f":"F5-E5","v":{"$error":"#NAME?"}},{"$f":"G5/E5","v":{"$error":"#NAME?"}}]
[]
[{"$f":"\"Four Highest \"&'P155(3)'!D2","v":"Four Highest #Desserts Out per Month"},null,null,null,"From the market research data and our analysis, site Y has a large average for both # of deserts per month and # of meals per month. Although the variation (standard deviation) for the # of meals per month for the Y site is slight higher than it is for the X site, the reverse is true for the # of deserts per month. Lower variation is a great benifit becasue it reduced future uncertainty and helps with planning, but in this case each site has a lower variation and so this statistic will not be used to determine which site should be slected. Thre same trade off can be seen in the low and high analysis. In the end, the dramatic difference in the larger average # of meals per month and larger averange # of deserts per month for the Y site points toward selecting the Y site. A dollar sales per # of deserts and meals might be a next step in the analysis."]
[null,"SiteX","SiteY"]
[1,{"$f":"LARGE(xd,$A9)","v":{"$error":"#NAME?"}},{"$f":"LARGE(yd,$A9)","v":{"$error":"#NAME?"}}]
[2,{"$f":"LARGE(xd,$A10)","v":{"$error":"#NAME?"}},{"$f":"LARGE(yd,$A10)","v":{"$error":"#NAME?"}}]
[3,{"$f":"LARGE(xd,$A11)","v":{"$error":"#NAME?"}},{"$f":"LARGE(yd,$A11)","v":{"$error":"#NAME?"}}]
[4,{"$f":"LARGE(xd,$A12)","v":{"$error":"#NAME?"}},{"$f":"LARGE(yd,$A12)","v":{"$error":"#NAME?"}}]
[]
[{"$f":"\"Ten Lowest \"&'P155(3)'!F2","v":"Ten Lowest # Meals out per Month"}]
[null,"SiteX","SiteY"]
[1,{"$f":"SMALL(xm,$A16)","v":{"$error":"#NAME?"}},{"$f":"SMALL(ym,$A16)","v":{"$error":"#NAME?"}}]
[2,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[3,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[4,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[5,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[6,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[7,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[8,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[9,{"$error":"#NAME?"},{"$error":"#NAME?"}]
[10,{"$error":"#NAME?"},{"$error":"#NAME?"}]

{"sheet":"P156(2)","index":44,"n_rows":7,"n_cols":3,"rows_kept":7,"cut":false,"hidden":false,"merged":[]}
["Site Y Demographic Analysis"]
[null,"Total number of respondents =",{"$f":"COUNT('P155(4)'!A3:A109)","v":107}]
[{"$f":"\">=\"&'P155(2)'!B17","v":">=75000"},{"$f":"\"Total number of respondents with incomes at or above \"&DOLLAR('P155(2)'!B17)&\" =\"","v":"Total number of respondents with incomes at or above $75,000.00 ="},{"$f":"COUNTIF('P155(4)'!C3:C109,A3)","v":26}]
["<5","Total number of respondents who eat less than 5 desserts out each month =",{"$f":"COUNTIF(yd,A4)","v":{"$error":"#NAME?"}}]
[{"$f":"\"<\"&'P155(2)'!B17","v":"<75000"},{"$f":"\"Total number of meals eaten out per month reported by respondents who earn below \"&DOLLAR('P155(2)'!B17)&\" =\"","v":"Total number of meals eaten out per month reported by respondents who earn below $75,000.00 ="},{"$f":"SUMIF('P155(4)'!C3:C109,A5,ym)","v":{"$error":"#NAME?"}}]
[{"$f":"'P155(2)'!A13","v":"26-30"},{"$f":"\"Total number of desserts eaten out per month reported by respondents who are in the \"&A6&\" age category or in the \"&A7&\" age category =\"","v":"Total number of desserts eaten out per month reported by respondents who are in the 26-30 age category or in the 30-35 age category ="},{"$f":"SUMIF('P155(4)'!B3:B109,A6,yd)+SUMIF('P155(4)'!B3:B109,A7,yd)","v":{"$error":"#NAME?"}}]
[{"$f":"'P155(2)'!A14","v":"30-35"}]

{"sheet":"Case 3==>","index":45,"n_rows":0,"n_cols":0,"rows_kept":0,"cut":false,"hidden":false,"merged":[]}

{"sheet":"Assumptions","index":46,"n_rows":23,"n_cols":3,"rows_kept":23,"cut":false,"hidden":false,"merged":[]}
["CKG Auto Parts Supply"]
[]
["Assumptions/Inputs, Information, Directions"]
[null,"Each warehousing distribution center serves a different set of customers and thus has different needs and demands"]
[null,"Each distribution Center has a 5 day lead time for ordering parts",5]
[null,"# of Standard Deviations to add to the mean when determining target inventory levels",2]
[null,"Reducing inventory cost is important but must balanced with having enough parts to supply auto repair shops and keep customers happy"]
[null,"Bearings are a part that is particularly problematic"]
[null,"They are large and take up space"]
[null,"They are high volume"]
[null,"They are expensive and use up working capital"]
[null,"We will analyzing bearings in the New Jersey warehouse (which serves 10 major customers)"]
[null,"We will simulate bearing inventory demand based on 30-day historical extremes"]
[null,"The key to maximizing profits is to:"]
[1,"Key component for Auto Supply is to have enough of the right parts for same-day delivery to repair shops"]
[2,"Lower Inventory costs by not warehousing: 1) Parts for too long and 2) Too many of the same parts"]
[null,"Goals:"]
[1,"Determine target inventory levels based on the simulation"]
[2,"Compare simulated values to actual values from the past five days"]
[null,"Determine target inventory levels based on the simulation"]
[null,"Costs of inventory warehousing:"]
[1,"Working Capital (cost of each part)"]
[2,"Space to store part"]

{"sheet":"BearingData","index":47,"n_rows":36,"n_cols":11,"rows_kept":36,"cut":false,"hidden":false,"merged":[]}
["Orders for a sample 30-Day Period"]
[null,"Customer#"]
["Day",1234,3093,1780,2121,4537,1141,5292,1330,3390,8540]
[1,8,5,9,3,4,12,5,7,13,8]
[2,5,5,10,3,4,0,1,10,6,4]
[3,2,6,6,4,16,4,10,2,7,2]
[4,3,0,2,4,5,11,10,10,12,8]
[5,3,8,7,4,11,3,1,9,8,8]
[6,14,8,3,1,12,11,2,8,13,6]
[7,5,4,5,3,10,2,2,5,9,5]
[8,11,9,9,6,5,10,5,10,12,2]
[9,9,4,7,2,10,9,4,3,8,2]
[10,11,9,4,3,8,0,0,9,6,2]
[11,10,0,8,0,9,12,9,1,13,7]
[12,2,3,9,6,13,3,9,5,7,5]
[13,5,1,9,6,14,8,3,1,8,8]
[14,7,6,3,2,15,9,0,7,2,3]
[15,3,4,4,6,13,8,1,2,13,3]
[16,6,7,2,6,9,3,3,10,10,6]
[17,2,5,9,3,10,0,5,5,9,7]
[18,2,1,4,5,7,12,10,9,6,4]
[19,13,6,5,6,6,12,1,0,7,8]
[20,4,5,7,2,8,3,0,9,8,5]
[21,14,0,3,2,12,10,7,7,4,8]
[22,4,9,4,4,12,5,10,4,7,2]
[23,13,4,8,0,7,1,0,9,12,5]
[24,5,1,2,6,6,4,7,4,13,5]
[25,10,0,2,2,7,1,6,7,4,2]
[26,11,9,3,0,13,2,5,6,2,3]
[27,14,9,9,3,11,10,0,4,13,2]
[28,12,9,3,2,12,9,0,7,13,2]
[29,14,1,3,0,12,7,0,2,7,8]
[30,10,1,8,1,14,5,7,3,2,2]
[]
["Max",{"$f":"MAX(B4:B33)","v":14},{"$f":"MAX(C4:C33)","v":9},10,6,16,12,10,10,13,8]
["Min",{"$f":"MIN(B4:B33)","v":2},{"$f":"MIN(C4:C33)","v":0},2,0,4,0,0,0,2,2]

{"sheet":"Simulation (2)","index":48,"n_rows":107,"n_cols":11,"rows_kept":107,"cut":false,"hidden":false,"merged":[]}
["Simulation based on max and min from \"Orders for a sample 30-Day Period\""]
[null,"Customer#"]
["Day",1234,3093,1780,2121,4537,1141,5292,1330,3390,8540]
[{"$f":"ROW()-ROWS($A$1:$A$3)","v":1},{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":4},5,9,4,14,8,9,4,3,6]
[2,12,3,7,3,11,2,0,4,5,7]
[3,13,9,8,2,9,10,2,6,9,4]
[4,9,2,5,2,10,1,0,5,5,6]
[5,4,2,4,1,10,11,10,4,12,3]
[6,7,7,6,5,5,8,9,7,3,8]
[7,5,7,9,3,15,3,0,5,5,4]
[8,6,3,8,3,5,4,7,3,10,8]
[9,8,3,7,0,5,10,7,6,10,6]
[10,8,0,9,6,9,12,10,6,4,4]
[11,11,6,6,2,15,10,4,1,3,8]
[12,8,8,9,3,9,6,7,10,12,7]
[13,11,0,8,4,4,7,2,5,7,5]
[14,4,2,10,0,12,5,3,6,7,5]
[15,3,7,4,1,11,8,8,5,6,3]
[16,4,3,9,2,9,2,9,5,2,6]
[17,{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":13},4,10,3,8,8,2,3,4,4]
[18,2,3,8,1,5,4,8,7,12,4]
[19,13,1,3,1,12,6,3,2,4,3]
[20,14,1,8,2,16,6,4,6,4,5]
[21,7,8,9,2,7,9,7,6,12,6]
[22,14,6,4,2,6,8,9,10,5,8]
[23,8,4,7,5,7,3,7,6,3,6]
[24,11,8,9,1,10,4,2,5,11,6]
[25,5,1,5,3,5,0,3,8,3,3]
[26,7,1,9,3,9,3,6,7,3,2]
[27,11,6,9,2,11,4,10,9,8,6]
[28,9,5,10,2,11,5,9,4,9,5]
[29,3,0,5,4,16,0,8,7,12,5]
[30,5,8,6,5,12,7,2,9,3,6]
[31,10,5,8,3,13,3,7,10,9,5]
[32,6,2,10,5,11,11,4,5,10,7]
[33,{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":9},3,8,2,10,0,7,4,4,3]
[34,13,4,6,6,13,4,3,4,4,5]
[35,11,1,7,3,14,5,6,6,7,4]
[36,11,2,3,1,7,3,7,6,4,6]
[37,6,6,7,4,9,3,3,8,5,2]
[38,8,8,7,2,7,1,9,3,6,2]
[39,10,0,7,6,14,0,2,4,11,3]
[40,8,6,9,2,9,4,4,1,12,3]
[41,13,9,7,5,8,10,5,9,10,6]
[42,11,4,8,5,12,12,7,5,13,7]
[43,8,6,3,3,5,2,4,7,11,7]
[44,6,4,10,4,10,2,4,3,7,3]
[45,12,8,5,6,8,12,2,10,5,5]
[46,5,2,3,4,8,10,8,3,8,8]
[47,2,2,9,6,7,8,9,3,9,7]
[48,6,7,9,2,7,1,2,8,8,3]
[49,{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":10},7,9,3,15,1,10,5,7,4]
[50,7,5,8,2,14,10,1,5,3,3]
[51,6,7,8,4,14,4,1,8,6,7]
[52,5,6,7,6,11,4,6,7,7,5]
[53,14,3,9,3,11,6,7,9,3,5]
[54,2,1,5,5,14,8,6,9,13,2]
[55,4,6,2,1,12,7,2,8,10,6]
[56,11,1,7,1,6,1,4,9,7,3]
[57,12,7,6,4,15,0,10,2,13,3]
[58,12,5,5,2,9,7,5,3,5,4]
[59,6,1,3,5,6,0,5,5,2,4]
[60,13,8,7,5,14,4,7,2,3,7]
[61,4,7,4,1,7,0,5,9,13,2]
[62,9,3,7,0,13,11,5,4,10,3]
[63,11,8,4,4,10,8,8,4,8,3]
[64,6,7,4,3,10,0,7,2,10,2]
[{"$f":"ROW()-ROWS($A$1:$A$3)","v":65},{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":12},1,9,1,10,2,5,9,5,6]
[66,11,7,3,3,5,4,1,9,5,4]
[67,4,6,2,2,10,8,6,0,10,7]
[68,12,1,4,5,6,7,2,2,12,3]
[69,11,0,3,6,7,11,4,6,6,6]
[70,8,7,3,4,13,7,3,3,8,4]
[71,11,5,2,4,4,3,8,7,7,3]
[72,8,7,2,4,13,7,3,10,8,6]
[73,13,7,6,3,5,7,9,2,8,5]
[74,14,1,3,3,5,12,3,9,11,6]
[75,2,5,9,2,16,1,4,4,2,6]
[76,4,0,7,3,15,8,3,8,11,7]
[77,3,4,7,2,5,2,5,9,4,6]
[78,5,2,4,3,11,8,8,10,11,5]
[79,3,6,9,3,5,10,4,9,6,7]
[80,3,0,9,6,13,10,0,3,7,3]
[81,{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":11},0,7,4,8,7,9,6,9,3]
[82,13,6,8,4,16,2,5,0,10,4]
[83,11,3,8,3,13,0,10,9,13,7]
[84,6,9,5,6,12,6,3,8,6,8]
[85,6,3,5,6,5,6,6,8,3,7]
[86,8,2,4,2,6,12,8,3,3,7]
[87,13,1,5,3,11,3,6,1,9,4]
[88,9,7,8,4,11,6,7,6,5,5]
[89,13,4,8,3,16,2,8,2,3,5]
[90,8,5,7,4,10,7,9,7,12,7]
[91,5,2,9,4,7,10,4,7,10,5]
[92,5,4,9,3,7,5,5,7,7,4]
[93,11,6,3,4,8,7,5,7,3,8]
[94,4,5,4,0,11,12,8,8,6,6]
[95,8,2,6,0,6,10,6,5,11,3]
[96,14,6,5,1,15,9,7,6,7,2]
[97,{"$f":"ROUND(B$107+RAND()*(B$106-B$107),0)","v":7},8,7,5,15,6,8,0,8,6]
[98,7,2,5,4,9,7,10,5,6,7]
[99,4,2,7,1,8,6,5,6,2,2]
[100,5,9,5,4,14,4,3,3,5,8]
[]
[]
["Max",{"$f":"BearingData!B35","v":14},{"$f":"BearingData!C35","v":9},{"$f":"BearingData!D35","v":10},{"$f":"BearingData!E35","v":6},{"$f":"BearingData!F35","v":16},{"$f":"BearingData!G35","v":12},{"$f":"BearingData!H35","v":10},{"$f":"BearingData!I35","v":10},{"$f":"BearingData!J35","v":13},{"$f":"BearingData!K35","v":8}]
["Min",{"$f":"BearingData!B36","v":2},{"$f":"BearingData!C36","v":0},{"$f":"BearingData!D36","v":2},{"$f":"BearingData!E36","v":0},{"$f":"BearingData!F36","v":4},{"$f":"BearingData!G36","v":0},{"$f":"BearingData!H36","v":0},{"$f":"BearingData!I36","v":0},{"$f":"BearingData!J36","v":2},{"$f":"BearingData!K36","v":2}]

{"sheet":"Simulation Data 1","index":49,"n_rows":114,"n_cols":18,"rows_kept":114,"cut":false,"hidden":false,"merged":[]}
["(Values Not Randomizable numbers) Simulation based on max and min from \"Orders for a sample 30-Day Period\""]
[null,"Customer#"]
["Day",1234,3093,1780,2121,4537,1141,5292,1330,3390,8540,"Totals","Mean","Median","Mode","StDev","Skew","Rank"]
[1,11,6,6,2,4,0,1,2,12,3,{"$f":"SUM(B4:K4)","v":47},{"$f":"AVERAGE(B4:K4)","v":4.7},{"$f":"MEDIAN(B4:K4)","v":3.5},{"$f":"MODE(B4:K4)","v":6},{"$f":"STDEV(B4:K4)","v":4.0838435055444737},{"$f":"SKEW(B4:K4)","v":0.90613976098510796},{"$f":"RANK(L4,L$4:L$103,1)","v":10}]
[2,3,2,6,2,5,2,5,4,5,5,{"$f":"SUM(B5:K5)","v":39},3.9,4.5,5,1.5238839267549951,-0.26374310309442883,3]
[3,12,3,6,5,5,6,2,3,13,7,{"$f":"SUM(B6:K6)","v":62},6.2,5.5,3,3.6757463338907259,1.0262416403951347,59]
[4,13,5,8,0,11,1,2,0,5,4,49,4.9000000000000004,4.5,5,4.5325979795746774,0.69874217281293549,15]
[5,10,7,2,1,4,10,6,2,5,7,54,5.4,5.5,10,3.2041639575194436,0.15402036226902333,29]
[6,3,5,7,3,11,3,4,4,6,8,54,5.4,4.5,3,2.6331223544175328,1.1448093446420529,29]
[7,9,4,8,2,10,9,9,9,12,6,78,7.8,9,9,2.9739610697593952,-0.86682017241225784,98]
[8,6,3,6,0,14,5,4,4,6,6,{"$f":"SUM(B11:K11)","v":54},5.4,5.5,6,3.5652645218989165,1.4100210156132789,29]
[9,3,3,2,4,8,1,6,10,10,7,54,5.4,5,3,3.2727833889689535,0.24437686093618766,29]
[10,12,5,9,4,10,9,4,10,8,8,79,7.9,8.5,9,2.7264140062238038,-0.36267024575540396,99]
[11,13,1,5,1,12,11,3,1,7,5,59,5.9,5,1,4.6773686809762793,0.46157660179060722,45]
[12,11,2,5,2,11,2,7,2,6,8,56,5.6,5.5,2,3.6270588023294512,0.42124258383689805,35]
[13,14,6,8,5,7,10,6,8,7,3,74,7.4,7,6,2.9888682361946519,1.0449220512760029,93]
[14,6,5,5,2,9,5,9,2,9,6,58,5.8,5.5,5,2.6161889160464784,-0.10052294441505046,43]
[15,13,3,8,1,5,10,2,5,11,7,65,6.5,6,5,4.0069384267237691,0.22668291886196057,65]
[16,14,5,4,3,12,11,0,6,5,5,65,6.5,5,5,4.4032816045409691,0.54660978038488528,65]
[17,11,3,3,4,14,6,4,8,5,5,63,6.3,5,3,3.6530048514126623,1.3238334526462663,61]
[18,9,9,4,4,9,11,2,5,6,7,66,6.6,6.5,9,2.8751811537130427,-5.8902319421150061E-2,73]
[19,12,5,5,1,5,10,8,3,4,4,57,5.7,5,5,3.3349995835415371,0.77643505630091125,39]
[20,4,0,5,3,4,8,4,1,5,8,42,4.2,4,4,2.5733678754158378,1.7604173058816057E-2,5]
[21,11,0,5,5,9,4,3,8,5,7,57,5.7,5,5,3.1640339933558099,-5.103840121285199E-2,39]
[22,4,3,10,1,7,4,2,5,6,7,49,4.9000000000000004,4.5,4,2.6853512081497111,0.43378647297253825,15]
[23,7,0,3,4,4,7,7,7,3,5,47,4.7,4.5,7,2.359378449224852,-0.69413389421958194,10]
[24,12,7,4,1,11,11,5,3,3,3,60,6,4.5,3,4,0.546875,50]
[25,9,2,2,2,13,5,2,5,11,2,53,5.3,3.5,2,4.2176876234364356,0.94897934504093207,26]
[26,2,4,5,2,14,7,9,6,5,5,59,5.9,5,5,3.5418137224371984,1.3594392033248368,45]
[27,9,9,7,5,9,2,8,1,8,7,65,6.5,7.5,9,2.9154759474226504,-1.1601374877287363,65]
[28,3,2,10,4,12,8,6,2,12,6,65,6.5,6,2,3.8658045015810671,0.33176221935598488,65]
[29,2,6,8,5,13,10,1,5,5,7,62,6.2,5.5,5,3.5527766918597945,0.48241378486612246,59]
[30,4,6,4,0,15,3,7,1,13,6,59,5.9,5,4,4.8177911028926017,0.93359088495188125,45]
[31,13,5,2,4,11,11,8,9,10,2,75,7.5,8.5,2,3.9791121287711073,-0.26453931050001822,94]
[32,7,4,2,4,9,2,8,7,4,3,50,5,4,4,2.5385910352879693,0.35656488233459155,17]
[33,9,1,7,4,10,3,9,6,13,5,67,6.7,6.5,9,3.622460796505909,0.14480638740915955,75]
[34,6,5,7,1,8,11,2,4,6,6,56,5.6,6,6,2.8751811537130427,0.15146310708295849,35]
[35,8,3,8,4,8,7,6,3,10,8,65,6.5,7.5,8,2.4152294576982398,-0.44361357386294181,65]
[36,7,5,6,6,15,8,2,5,5,2,61,6.1,5.5,5,3.6651512019742554,1.6099593418396982,53]
[37,6,4,3,1,11,3,9,7,11,4,59,5.9,5,4,3.5103022978402043,0.37336961469602842,45]
[38,11,8,4,2,14,8,3,6,7,6,69,6.9,6.5,8,3.6347092196090611,0.65564943269471421,81]
[39,5,8,3,4,9,7,0,0,7,2,45,4.5,4.5,7,3.2403703492039302,-0.14695557139246851,6]
[40,6,5,3,4,7,7,2,2,11,8,55,5.5,5.5,7,2.8771127502720115,0.48986469960939599,33]
[41,11,3,9,5,11,11,8,6,3,8,75,7.5,8,11,3.1358146203711299,-0.31078886642575154,94]
[42,6,6,5,1,15,9,8,8,4,7,69,6.9,6.5,6,3.6651512019742554,0.86117253272501892,81]
[43,12,0,6,1,9,4,4,6,5,4,51,5.0999999999999996,4.5,4,3.5103022978402043,0.58991628493252835,21]
[44,7,6,8,2,8,1,8,8,7,5,60,6,7,8,2.5819888974716112,-1.2587195875174106,50]
[45,11,1,6,2,14,3,8,6,2,5,{"$f":"SUM(B48:K48)","v":58},5.8,5.5,6,4.2110964526276682,0.85524133676662872,43]
[46,13,7,5,3,13,10,10,2,6,6,75,7.5,6.5,13,3.8658045015810671,0.201942220477556,94]
[47,2,1,5,4,8,4,9,4,8,8,53,5.3,4.5,4,2.7908580918579311,-7.8971922660483834E-2,26]
[48,7,1,3,1,8,0,5,3,4,5,37,3.7,3.5,1,2.6267851073127395,0.22345052897745402,1]
[49,4,0,5,4,4,12,1,3,9,8,50,5,4,4,3.6817870057290869,0.65118948485500028,17]
[50,4,1,4,6,5,4,1,8,8,6,47,4.7,4.5,4,2.4517567397911053,-0.24540101233828121,10]
[51,6,2,8,0,15,9,2,6,4,5,57,5.7,5.5,6,4.2959929650263113,0.98232194468477851,39]
[52,9,5,5,1,10,3,1,9,5,3,51,5.0999999999999996,5,5,3.2812599206199229,0.31419630790090064,21]
[53,5,1,6,2,8,10,8,4,5,3,52,5.2,5,5,2.8596814119369629,0.2123792370669596,25]
[54,11,8,8,4,11,5,9,7,12,6,81,8.1,8,11,2.6853512081497102,-3.4427497854959644E-3,100]
[55,8,0,7,3,13,4,0,2,6,5,48,4.8,4.5,0,3.9665266081716042,0.77235315041692498,13]
[56,6,3,3,2,8,2,9,5,4,3,45,4.5,3.5,3,2.4608038433722332,0.89476244452218257,6]
[57,4,5,3,4,7,4,9,1,12,4,53,5.3,4,4,3.1989581637360209,1.0854511143489902,26]
[58,4,3,3,4,4,2,4,10,5,6,45,4.5,4,4,2.2236106773543889,1.8569858137481734,6]
[59,3,5,4,1,8,10,3,4,11,8,57,5.7,4.5,3,3.3349995835415371,0.37204179781085356,39]
[60,3,2,6,4,4,2,2,2,4,8,37,3.7,3.5,2,2.0027758514399734,1.240660327090408,1]
[61,13,6,5,5,4,0,9,9,11,7,69,6.9,6.5,5,3.7549966711037173,-0.13882211927273491,81]
[62,9,6,7,1,16,1,7,1,4,4,56,5.6,5,1,4.623610902506587,1.2218087806882347,35]
[63,8,8,6,1,10,6,1,9,11,8,68,6.8,8,8,3.4253953543107016,-0.92806141887437188,80]
[64,4,1,3,3,9,3,6,9,4,8,50,5,4,3,2.8284271247461903,0.40511326005479281,17]
[65,13,4,3,4,11,6,7,5,6,8,67,{"$f":"AVERAGE(B68:K68)","v":6.7},{"$f":"MEDIAN(B68:K68)","v":6},{"$f":"MODE(B68:K68)","v":4},{"$f":"STDEV(B68:K68)","v":3.1989581637360209},{"$f":"SKEW(B68:K68)","v":1.0019548747836828},{"$f":"RANK(L68,L$4:L$103,1)","v":75}]
[66,3,8,7,2,4,5,7,7,11,7,61,6.1,7,7,2.6436506745197796,0.13621141135546094,53]
[67,6,5,8,2,14,7,4,3,12,8,{"$f":"SUM(B70:K70)","v":69},6.9,6.5,8,3.8137179293236203,0.71181658831736838,81]
[68,10,2,8,6,13,6,1,1,6,8,61,6.1,6,6,3.9285281382896229,0.15421336239711542,53]
[69,13,5,10,1,8,10,4,5,13,3,{"$f":"SUM(B72:K72)","v":72},7.2,6.5,13,4.2110964526276682,0.12676854887355044,89]
[70,8,7,10,6,7,12,7,4,2,4,67,6.7,7,7,2.9458068127047605,0.23666966061206643,75]
[71,4,4,8,1,11,5,6,5,5,2,51,5.0999999999999996,5,5,2.8460498941515411,0.77791741251513014,21]
[72,3,8,8,3,15,1,4,1,13,5,61,6.1,4.5,3,4.8407988321488151,0.87141607721049097,53]
[73,4,3,7,6,8,1,7,5,8,6,55,5.5,6,7,2.2730302828309759,-0.85149937754334182,33]
[74,9,0,6,2,14,12,2,7,4,5,61,6.1,5.5,2,4.508017549014447,0.52776390484520386,53]
[75,8,9,4,6,16,11,0,8,4,7,73,7.3,7.5,8,4.3474130238568316,0.4253578712348377,92]
[76,2,4,10,0,13,0,9,2,6,2,48,4.8,3,2,4.5166359162544856,0.72390334394024913,13]
[77,6,7,7,5,10,3,4,9,12,7,70,7,7,7,2.7487370837451071,0.40125379142040363,86]
[78,8,5,5,2,11,8,8,0,12,6,65,6.5,7,8,3.7193189340702331,-0.28344352451544097,65]
[79,10,6,7,2,7,9,7,8,9,2,67,6.7,7,7,2.7507574714370349,-0.97049760000631291,75]
[80,13,5,7,2,13,5,7,0,10,8,70,7,7,13,4.2687494916218993,-4.285255661577634E-2,86]
[81,3,8,4,2,10,2,4,2,2,4,41,4.0999999999999996,3.5,2,2.766867462592951,1.4839708474046682,4]
[82,7,1,8,4,10,10,10,7,11,4,72,7.2,7.5,10,3.2930904093942588,-0.71031737774018899,89]
[83,4,7,9,5,8,5,8,10,12,4,72,7.2,7.5,4,2.6997942308422123,0.37096323075387572,89]
[84,7,4,7,6,13,4,5,8,7,6,67,6.7,6.5,7,2.5841396591085748,1.6689546808476385,75]
[85,4,6,2,6,14,3,9,8,4,4,60,6,5,4,3.5590260840104371,1.330937732247671,50]
[86,9,5,8,4,13,6,7,7,12,6,77,7.7,7,6,2.907843798341919,0.84596055598855224,97]
[87,4,3,10,1,7,9,3,1,2,6,46,4.5999999999999996,3.5,3,3.2386554137309651,0.5720751363152109,9]
[88,7,5,6,2,11,8,10,4,9,8,70,7,7.5,8,2.7888667551135851,-0.38418062442891215,86]
[89,5,8,6,4,9,10,6,9,7,2,66,6.6,6.5,6,2.5033311140691445,-0.43983946973657101,73]
[90,12,5,7,4,9,3,6,3,3,4,56,5.6,4.5,3,2.9888682361946519,1.2646428171357145,35]
[91,14,0,10,2,13,1,1,6,11,7,65,6.5,6.5,1,5.3176853778479387,0.12191959713146371,65]
[92,9,5,4,2,14,5,3,10,4,5,61,6.1,5,5,3.7252889522529355,1.2237566363557075,53]
[93,9,2,9,1,5,5,9,3,5,3,51,5.0999999999999996,5,9,2.9981475762358474,0.31292499084415154,21]
[94,8,5,9,5,16,1,3,9,7,6,69,6.9,6.5,5,4.0947120370871826,0.99993195187298345,81]
[95,6,8,8,4,13,3,0,9,4,8,63,6.3,7,8,3.6832956257496723,6.9041364076769265E-2,61]
[96,10,6,3,1,14,11,6,5,6,2,64,6.4,6,6,4.1419265512024177,0.58263042702497814,63]
[97,3,9,6,5,7,2,9,1,5,3,{"$f":"SUM(B100:K100)","v":50},5,5,3,2.7888667551135851,0.19209031221445627,17]
[98,10,8,5,4,9,4,3,6,9,7,{"$f":"SUM(B101:K101)","v":65},6.5,6.5,4,2.4608038433722332,-1.0842021724855044E-17,65]
[99,7,7,3,5,9,6,3,8,8,3,{"$f":"SUM(B102:K102)","v":59},5.9,6.5,3,2.2827858224351902,-0.26760031292588937,45]
[100,10,3,6,4,4,5,10,9,8,5,{"$f":"SUM(B103:K103)","v":64},6.4,5.5,10,2.6331223544175328,0.3231758437027803,63]
["Totals",{"$f":"SUM(B4:B103)","v":768},437,590,297,984,581,518,508,725,{"$f":"SUM(K4:K103)","v":545},{"$f":"SUM(B104:K104)","v":5953}]
[]
["Bearing Recommendation"]
[{"$f":"\"Suggested Target Inventory Level for a \"&Assumptions!C5&\" day period = ((Mean from simulation + \"&Assumptions!C6&\" Standard Deviations)*\"&Assumptions!C5&\" =\"","v":"Suggested Target Inventory Level for a 5 day period = ((Mean from simulation + 2 Standard Deviations)*5 ="},null,null,null,null,{"$f":"ROUNDUP((L107+Assumptions!C6*L110)*Assumptions!C5,0)","v":396},null,null,null,null,"Mean",{"$f":"AVERAGE(L4:L103)","v":59.53}]
[null,null,null,null,null,null,null,null,null,null,"Median",{"$f":"MEDIAN(L4:L103)","v":60}]
["Top Five Total Demand",null,"Lowest Five Total Demand",null,null,null,null,null,null,null,"Mode",{"$f":"MODE(L4:L103)","v":65}]
[1,{"$f":"LARGE($L4:$L103,A110)","v":81},1,{"$f":"SMALL($L4:$L103,C110)","v":37},null,null,null,null,null,null,"StDev",{"$f":"STDEV(L4:L103)","v":9.8210812217207586}]
[2,{"$f":"LARGE($L5:$L104,A111)","v":81},2,{"$f":"SMALL($L5:$L104,C111)","v":37},null,null,null,null,null,null,"Skew",{"$f":"SKEW(L4:L103)","v":-0.1166710585336227}]
[3,{"$f":"LARGE($L6:$L105,A112)","v":79},3,{"$f":"SMALL($L6:$L105,C112)","v":41}]
[4,{"$f":"LARGE($L7:$L107,A113)","v":78},4,{"$f":"SMALL($L7:$L107,C113)","v":42}]
[5,{"$f":"LARGE($L8:$L108,A114)","v":77},5,{"$f":"SMALL($L8:$L108,C114)","v":45}]

{"sheet":"Actual Demand","index":50,"n_rows":992,"n_cols":10,"rows_kept":992,"cut":false,"hidden":false,"merged":[]}
["Description","Value","#Days in Inventory",null,"Description","# of Items Shipped","Total Dollar Value of Items Shipped","Average # of Days Held In Inventory"]
["Air Filters",2.25,28,null,"Air Filters",{"$f":"COUNTIF(item,E2)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E2,cost)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E2,DaysInInv)/COUNTIF(item,E2)","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,13,null,"Bearings",{"$f":"COUNTIF(item,E3)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E3,cost)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E3,DaysInInv)/COUNTIF(item,E3)","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,5,null,"Electronic Board",{"$f":"COUNTIF(item,E4)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E4,cost)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E4,DaysInInv)/COUNTIF(item,E4)","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,16,null,"Fan Belt",{"$f":"COUNTIF(item,E5)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E5,cost)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E5,DaysInInv)/COUNTIF(item,E5)","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,36,null,"Timing Belts",{"$f":"COUNTIF(item,E6)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E6,cost)","v":{"$error":"#NAME?"}},{"$f":"SUMIF(item,E6,DaysInInv)/COUNTIF(item,E6)","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,21]
["Air Filters",2.25,25,null,null,"Data"]
["Air Filters",2.25,5,null,"Description","Count of Description","Sum of Value","Average of #Days in Inventory"]
["Air Filters",2.25,23,null,"Air Filters",232,4302.6000000000004,18.387931034482758]
["Air Filters",2.25,31,null,"Bearings",322,25363.200000000001,19.819875776397517]
["Air Filters",34.950000000000003,22,null,"Electronic Board",12,1500,22.916666666666668]
["Air Filters",2.25,1,null,"Fan Belt",226,3635.1300000000074,21.659292035398231]
["Air Filters",2.25,40,null,"Timing Belts",199,6955.0499999999765,19.849246231155778]
["Air Filters",2.25,3,null,"Grand Total",991,41755.979999999043,19.947527749747728]
["Air Filters",34.950000000000003,16]
["Air Filters",2.25,30,null,{"$f":"'Simulation Data 1'!A106","v":"Bearing Recommendation"}]
["Air Filters",34.950000000000003,23,null,{"$f":"'Simulation Data 1'!A107","v":"Suggested Target Inventory Level for a 5 day period = ((Mean from simulation + 2 Standard Deviations)*5 ="},null,null,null,null,{"$f":"'Simulation Data 1'!F107","v":396}]
["Air Filters",125,25]
["Air Filters",125,16,null,"Actual Data for Last Five Days"]
["Air Filters",2.25,25,null,{"$f":"E3","v":"Bearings"},null,null,null,null,{"$f":"F3","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,9,null,"Cost of Bearings (Working Capital)",null,null,null,null,{"$f":"G3","v":{"$error":"#NAME?"}}]
["Air Filters",125,14,null,{"$f":"H1","v":"Average # of Days Held In Inventory"},null,null,null,null,{"$f":"H3","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,23]
["Air Filters",2.25,3,null,{"$f":"\"Suggested Target Inventory Levels of \"&J18&\" would have covered the five day inventory Levels of \"&J21&\".\"","v":{"$error":"#NAME?"}}]
["Air Filters",2.25,29]
["Air Filters",2.25,29]
["Air Filters",2.25,3]
["Air Filters",2.25,3]
["Air Filters",125,14]
["Air Filters",2.25,31]
["Air Filters",2.25,27]
["Air Filters",2.25,25]
["Air Filters",2.25,2]
["Air Filters",125,14]
["Air Filters",2.25,2]
["Air Filters",2.25,39]
["Air Filters",2.25,6]
["Air Filters",125,23]
["Air Filters",2.25,10]
["Air Filters",2.25,11]
["Air Filters",2.25,2]
["Air Filters",2.25,20]
["Air Filters",2.25,18]
["Air Filters",2.25,1]
["Air Filters",2.25,16]
["Air Filters",2.25,2]
["Air Filters",2.25,33]
["Air Filters",2.25,18]
["Air Filters",2.25,15]
["Air Filters",2.25,7]
["Air Filters",2.25,34]
["Air Filters",125,16]
["Air Filters",2.25,14]
["Air Filters",2.25,22]
["Air Filters",2.25,25]
["Air Filters",2.25,14]
["Air Filters",2.25,12]
["Air Filters",2.25,19]
["Air Filters",2.25,21]
["Air Filters",2.25,9]
["Air Filters",125,11]
["Air Filters",2.25,17]
["Air Filters",2.25,17]
["Air Filters",2.25,15]
["Air Filters",2.25,23]
["Air Filters",2.25,31]
["Air Filters",2.25,15]
["Air Filters",2.25,19]
["Air Filters",2.25,16]
["Air Filters",2.25,3]
["Air Filters",2.25,13]
["Air Filters",2.25,32]
["Air Filters",2.25,37]
["Air Filters",2.25,11]
["Air Filters",2.25,35]
["Air Filters",2.25,8]
["Air Filters",2.25,18]
["Air Filters",2.25,27]
["Air Filters",2.25,16]
["Air Filters",2.25,1]
["Air Filters",2.25,6]
["Air Filters",125,35]
["Air Filters",2.25,21]
["Air Filters",2.25,28]
["Air Filters",2.25,28]
["Air Filters",2.25,31]
["Air Filters",125,21]
["Air Filters",2.25,14]
["Air Filters",2.25,18]
["Air Filters",2.25,39]
["Air Filters",2.25,4]
["Air Filters",2.25,34]
["Air Filters",2.25,13]
["Air Filters",2.25,11]
["Air Filters",125,10]
["Air Filters",2.25,28]
["Air Filters",2.25,6]
["Air Filters",2.25,28]
["Air Filters",2.25,14]
["Air Filters",2.25,4]
["Air Filters",2.25,24]
["Air Filters",2.25,4]
["Air Filters",125,3]
["Air Filters",2.25,18]
["Air Filters",2.25,18]
["Air Filters",2.25,11]
["Air Filters",2.25,2]
["Air Filters",2.25,35]
["Air Filters",2.25,8]
["Air Filters",2.25,31]
["Air Filters",2.25,21]
["Air Filters",2.25,9]
["Air Filters",125,13]
["Air Filters",2.25,18]
["Air Filters",125,40]
["Air Filters",2.25,5]
["Air Filters",2.25,22]
["Air Filters",2.25,6]
["Air Filters",2.25,33]
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