A baseball analyst would like to develop a model to predict the number
tutor4helpyouHomework #10
A baseball analyst would like to develop a model to predict the number of wins during the 2000 baseball season. The analyst collected several variables: Wins, ERA, Runs Scored, Hits Allowed, Walks Allowed, Errors, and Saves from 30 professional baseball teams.
Summary Output | Correlation Matrix | ||||
Regression Statistics |
|
| Wins | ERA | |
Win | 1 |
| |||
Multiple R | 0.9504 | ||||
ERA | -.6598 | 1 | |||
R squared | 0.9032 | Run Scored | .6101 | .0856 | |
Standard Error | 3.3463 | Hits Allowed | -.5520 | .8600 | |
Observations | 30 | Walks Allowed | -.2261 | .3105 | |
|
| Saves | .5320 | -.5985 | |
Errors | -.1308 | .0540 | |||
ANOVA
df SS MS F Significance F
Regression 4 2611.92 652.98 58.3123 2.59E-12
Residual 25 279.95 11.198
Total 29 2891.97
Coefficient Standard Error t Stat P-value Lower 95% Upper 95%
Interceptb0 74.771 16.7626 4.4610 0.0002 40.2540 109.3003
ERA b1 -12.3206 3.2066 -3.8423 0.0007 -18.9247 -5.7166
Run Scored b2 0.08433 0.0079 10.6414 9.0114E-11 0.0680 0.1007
Hits Allowed b3 -.0107 0.0163 -0.6563 0.5176 -0.0441 0.0228
Saves b4 0.2731 0.1203 2.2703 0.0321 0.0254 0.5208
Part C: Residual Analysis
13) Perform a residual analysis of the plots of the residuals versus the predicted Y’s, and each of the independent variables?
14) Is this model a good fit for the data? Explain
11 years ago
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