Guest on (OT 4. 5.00 points The following table lists Major League Baseball\'s (
ID: 3227633 • Letter: G
Question
Guest on (OT 4. 5.00 points The following table lists Major League Baseball's (MLB's) leading pitchers, their earned run average (ERA). and their salary (in $1,000,000s) for 2008. Salary (in $1,000,000s) J. Santana 2.52 11.0 C. Lee 2.38 3.0 T. Lincecum 2.23 0.4 C. Sabathia 2.15 9.0 2.02 R. Halladay 10.0 J. Peavy 2.68 5.0 D. Matsuzaka 8.3 R. Dempster 6.1 B. Sheets 10.9 C. Hamels 0.2 SOURCE: http:/www.ESPN.com. Click here for the Excel Data File a-1. Use Excel to estimate the model: Salary po sERA e. (Negative amounts should be indicated by a minus sign. Enter your answers in millions rounded to 2 decimal places.) Salary ERA a-2. Interpret the coefficient of ERA. G A one-unit increase in ERA, predicted salary decreases by $3.31 million. A one-unit increase in ERA, predicted salary increases by $3.31 million. A one-unit increase in ERA, predicted salary decreases by $11.32 million. A one-unit increase in ERA, predicted salary increases by s11.32 millionExplanation / Answer
a-1
Using excel :Data analysis.........> regression
Sale=14.6301-3.3146X
(b) Predicted values:
Ans:predicted values
Y^=14.6301-3.3146X=14.6301-3.3146(2.52)
Y^=14.6301-3.3146X=14.6301-3.3146(2.38)
Y^=14.6301-3.3146X=14.6301-3.3146(2.23)
Y^=14.6301-3.3146X=14.6301-3.3146(2.15
Y^=14.6301-3.3146X=14.6301-3.3146(2.02)
Y^=14.6301-3.3146X=14.6301-3.3146(2.68)
Y^=14.6301-3.3146X=14.6301-3.3146(2.68)
Y^=14.6301-3.3146X=14.6301-3.3146(2.56)
Y^=14.6301-3.3146X=14.6301-3.3146(2.68)
Y^=14.6301-3.3146X=14.6301-3.3146(2.96)
(c) residuals
SUMMARY OUTPUT Regression Statistics Multiple R 0.232389824 R Square 0.05400503 Adjusted R Square -0.064244341 Standard Error 4.250553279 Observations 10 ANOVA df SS MS F Significance F Regression 1 8.251374574 8.251375 0.456705 0.518222724 Residual 8 144.5376254 18.0672 Total 9 152.789 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 14.63010492 12.26698973 1.19264 0.267181 -13.65762411 42.91783 -13.6576 42.91783 X Variable 1 -3.314603749 4.904716734 -0.6758 0.518223 -14.62490081 7.995693 -14.6249 7.995693 RESIDUAL OUTPUT Observation Predicted Y Residuals 1 6.277303473 4.722696527 2 6.741347997 -3.741347997 3 7.23853856 -6.83853856 4 7.50370686 1.49629314 5 7.934605347 2.065394653 6 5.746966873 -0.746966873 7 5.746966873 2.553033127 8 6.144719323 -0.044719323 9 5.746966873 5.153033127 10 4.818877823 -4.618877823
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