HMKW 12 Data Analysis and Forecasting in the Sports and Health Industries Assignment

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HMKW12GROUP: ______________1HMKW 12Data Analysis and Forecasting in the Sports and HealthIndustries AssignmentGROUP1:HI206: Hockey Industry.The data in the templateHOCKEYis a data set fromTeemu Kivikko, WestlakeFall2000, who grew up playing youth hockey with TeemuSelanne of the Anaheim Ducks in Finland. Teemu used this data for his Econ class in2001 to check theprediction for2001 and 2002 sales.a)Take all variablesfromHOCKEYand place intoHI206a(R2)–makesure you use the correctdependent variable (Y).Hide rows 1214 and printA1:I19with row/column borders.Pay carefulattention to which data is history and which is forecasted.HINT: Color is a big clue. Print the tableand first two lines of data and hide the rows not used (don’t print blank columns).b)Eliminatetheweakervariablesthatshowcollinearityandprintthefinalcoefficientofdeterminationtable.Commentoneachvariable you eliminated and why.It shouldmakenodifferencewhichorderyoueliminate variables–the final result shouldbe the same. Print the revised R2 Table(A3:D6)using wrap-around.1Be sure to eliminate anyFIGURESandCheck Figuresfrom the homework. Answer the questions below and use this Word templateto cut and paste from the ExcelHMWK12.xlstemplate. Only show row/column headings if specified. Center or wrap-around Excelpictures or clip art and don’t indent.Print each problem starting on a separate page (use<Ctrl>+<Enter>)and label appropriately. Tryto keep each section question with the answer below it (no widows or orphans). Don’t try to cram too much information per page sothat it is miniscule and hard to read. Bonus points for appropriate clip art–up to 10% per problem and maximum 5 points bonus forprinting in color. Email me if you have questions–make sure you attach your spreadsheet and rename it with your name or group name–likeLUMATeers12.xls. Always place these instructions as a footnote (NOT footer!) on the first page of your group homeworkassignment (make sure it is 8 pt Comic Sans font or smaller font than body).12345678910111516171819ABCDEFGHIHI206abr2SalesYearUnemployWagesFed ExpMfgGERDPop 15-34Sales100.00%62.67%66.47%70.52%65.25%61.50%63.39%59.27%Year62.67%100.00%87.17%93.83%27.81%97.82%98.11%99.38%Unemploy66.47%87.17%100.00%93.70%33.35%86.67%83.60%83.56%Wages70.52%93.83%93.70%100.00%35.76%89.72%89.44%90.17%Fed Exp65.25%27.81%33.35%35.76%100.00%30.98%30.44%25.53%Mfg61.50%97.82%86.67%89.72%30.98%100.00%98.79%98.15%GERD63.39%98.11%83.60%89.44%30.44%98.79%100.00%98.14%Pop 15-3459.27%99.38%83.56%90.17%25.53%98.15%98.14%100.00%YX1X2X3X4X5X6X7SalesYearUnemployWagesFed ExpMfgGERDPop 15-34$165.50199110.40%379.091161.2070.156667710.7569,105,471$160.20199211.30%387.788164.4350.157680711.4019,035,736r2Table (Coefficient of Determination)Hockey Industry Sales/20r2SalesWagesFed ExpSales100.00%70.52%65.25%Wages70.52%100.00%35.76%Fed Exp65.25%35.76%100.00%

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HMKW12GROUP: ______________2The variables Year, Unemploy, Mfg, and GERD were eliminated because they have highcorrelation with the most of the other independent variables, i.e. r≥0.9 or r2≥0.81.

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HMKW12GROUP: ______________3c)For the templateHI206c, place the truly independent variables starting in X1 in order.Add onevariable at a time and Move/Copy the template and keep going.Give the prediction for 2001 and2002 using the estimates for the independent variables and commenton how these predictionscompare with what was given on the data sheet.PrintA1:G17.The predicted values for both the years 2001 and 2002 are much larger than theobserveddata values, yielding negative residuals.d)PrinttheSummaryTablebelowandcommentabouthowmuchithelpedtoaddthesecondindependent variable.CHECK FIGURE:$316.75in 2002for part c)Adding the second independent variable increases the explained variation up to 14% on thedependent variable.HI206cMinimizeRegression Forecast MeasuresDegrees ofR.M.S.E.R.M.S.E.M.A.D.M.A.P.E.FreedomModel19.2219.849.84%7n = 10Y-Bar (y)43.8535.9317.18%9$208.24Y-Bar (y)unbiased r280.79%69.52%67.20%biased r285.06%76.29%74.49%abcdefParameters-$603.29$0.46$3.642F =a+b*X1+c*X2+d*X3+e*X4+f*X52001291.7575.0172.62002316.7617.0174.1YFX1X2X3X4X5SalesModelWagesFed ExpX3X4X5$165.50159.5379.091161.207$160.20175.3387.788164.435Multiple Regression F = a + bX1 + cX2 + dX3 + eX4 + fX5Hockey IndustryOldNew2001$227.82$291.692002$250.10$316.75R.M.S.E.R.M.S.E.Degrees ofForecast ModelErrorUnbiased r2Freedoma+bX1+cX2+Y-Bar (y)43.850.00%9208.24Wages25.2566.84%8-98.880.70Fed Exp19.2280.79%7-603.290.463.64Multiple Regression Summary

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HMKW12GROUP: ______________4MSS206:MonthlySales Salary.This is an idea taken from a Virginia Tech web sitewhere I changed the values of the Independent variables. The data is shown on thetabSALARY.a)Enter the data fromSALARYinto the templateMSS206a(R2).PrintA1:E19with row and columnborders and a couple of lines of the data (hide rows814) and discuss which variable(s) are nottruly independent.The variable Intelligence is not truly independent.b)Move/Copy the template ina)and remove the collinear variable(s) and printA2:D6(you’ll need toreorderthevariables.Commentonwhichvariablesseemtobeabletopredictsuccessasasalesperson and which do not.The variables Extroversion and Exp (months) can successfully predict success as a salespersonand the variable Intelligence is not a significant predictor.c)Determine the optimal fit of the truly independent variables usingMSSG206cwith the data fromyourMSS206btemplate.Enter thebest independent variable first (highest r2), then Move/CopyMSS206cand enter the next best, and so on. What is the forecast fora sales person with 35 yearsexperience and anExtrovert score of 15, and another salesperson with 20 years experience andExtrovert score of 30and printA1:G17. What is an extra year of experience worth? What aboutanother point of Extrovert?12345671516171819ABCDEMSS206ar2$ Sales/WeekIntelligenceExtroversionExp (months)$ Sales/Week100.00%10.86%40.80%62.32%Intelligence10.86%100.00%5.85%10.99%Extroversion40.80%5.85%100.00%6.56%Exp (months)62.32%10.99%6.56%100.00%YX1X2X3$ Sales/WeekIntelligenceExtroversionExp (months)$2,625892127.4$2,700932529.3r2Table (Coefficient of Determination)Monthly Sales SalaryMSS206ar2$ Sales/WeekExtroversionExp (months)$ Sales/Week100.00%40.80%62.32%Extroversion40.80%100.00%6.56%Exp (months)62.32%6.56%100.00%Monthly Sales Salary/20

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