Question

1. What is the dependent variable in this model? 2. What is the R-Squared value of this regression model? 3. Interpret the R-Squared value in the context of this example. 4. What is the null hypothesis of the ANOVA in the output? 5. What is the alternative hypothesis of the ANOVA in the output? 6. Do you reject or not reject the null hypothesis of the ANOVA in this example? 7. Are any of the independent variables statistically significant at the ? = .05 level? If so, which one(s)? 8. If you were a manager at GoodBuy, would you market the insurance to younger or older consumers? Or does age really make much of a difference? 9. If you were a manager at GoodBuy, what would be the main takeaway of the study? 10. Show all the relevant regression output below: SUMMARY OUTPUT Regression Statistics Multiple R 0.43455223 R Square 0.18883564 Adjusted R Square 0.17890301 Standard Error 14.7512642 Observations 249 ANOVA df SS MS F Significance F Regression 3 12410.7969 4136.932 19.01166 4.0653E-11 Residual 245 53311.95009 217.5998 Total 248 65722.74699 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 69.6977922 6.613111218 10.53933 1.16E-21 56.67198723 82.72359716 56.67198723 82.72359716 AGE 0.21415436 0.133248764 1.607177 0.109303 -0.04830492 0.476613643 -0.04830492 0.476613643 LOYALTY -0.1707757 0.590458214 -0.28923 0.772653 -1.333797624 0.992246283 -1.333797624 0.992246283 SATISFACTION 3.15650861 0.427565145 7.382521 2.42E-12 2.314336142 3.998681076 2.314336142 3.998681076

          1. What is the dependent variable in this model?
2. What is the R-Squared value of this regression model?
3. Interpret the R-Squared value in the context of this example.
4. What is the null hypothesis of the ANOVA in the output?
5. What is the alternative hypothesis of the ANOVA in the output?
6. Do you reject or not reject the null hypothesis of the ANOVA in this example?
7. Are any of the independent variables statistically significant at the ? = .05 level? If so, which one(s)?
8. If you were a manager at GoodBuy, would you market the insurance to younger or older consumers? Or does age really make much of a difference?
9. If you were a manager at GoodBuy, what would be the main takeaway of the study?
10. Show all the relevant regression output below:

SUMMARY OUTPUT

Regression Statistics
Multiple R 0.43455223
R Square 0.18883564
Adjusted R Square 0.17890301
Standard Error 14.7512642
Observations 249

ANOVA
df SS MS F Significance F
Regression 3 12410.7969 4136.932 19.01166 4.0653E-11
Residual 245 53311.95009 217.5998
Total 248 65722.74699

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 69.6977922 6.613111218 10.53933 1.16E-21 56.67198723 82.72359716 56.67198723 82.72359716
AGE 0.21415436 0.133248764 1.607177 0.109303 -0.04830492 0.476613643 -0.04830492 0.476613643
LOYALTY -0.1707757 0.590458214 -0.28923 0.772653 -1.333797624 0.992246283 -1.333797624 0.992246283
SATISFACTION 3.15650861 0.427565145 7.382521 2.42E-12 2.314336142 3.998681076 2.314336142 3.998681076

Added by Tanya M.

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