Concept explainers
8. Use the multiple regression output shown to answer the following questions.
The regression equation is:
Y = 9.77 0.775X1 + 0.062X2 - 0.221X3
Predictor | Coef | SE Coef | T | P |
Constant | 9.771 | 7.132 | 1.37 | 0.184 |
X1 | 0.7747 | 0.3201 | 2.42 | 0.025 |
X2 | 0.0642 | 0.1686 | 0.37 | 0.716 |
X3 | -0.2214 | 0.1730 | -1.28 | 0.214 |
S = 5.04975 R - Sq = 14.9% R - Sq (adj) = 2.8%
Analysis of Variance | |||||
Source | DF | SS | MS | F | P |
---|---|---|---|---|---|
Regression | 3 | 94.1 | 31.35 | 1.23 | 0.322 |
Residual Error | 21 | 535.5 | 25.5 | ||
Total | 24 | 629.6 |
(a) What is R2 for this model? Do we expect to increase, decrease, or remain the same if we eliminate the variable chosen in part (a)? What type of change in would indicate that removing the variable in part (a) was a GOOD idea? What type of change in would indicate that removing the variable in part (a) was a BAD idea?
b) What is the p-value for ANOVA for the original 3-predictor model?
Is the p-value most likely to increase, decrease, or remain the same if we eliminate the variable chosen in part (a)? What type of change in the p-value for ANOVA would indicate that removing the variable in part (a) was a GOOD idea? What type of change in the p-value for ANOVA would indicate that removing the variable in part (a) was a BAD idea?
c) What is the F-statistic from ANOVA for this model? Is the F-statistic most likely to increase, decrease, or remain the same if we eliminate the variable chosen in part (a)? What type of change in the F-statistic for ANOVA would indicate that removing the variable in part (a) was a good idea?
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