The following output was obtained from a regression analysis of the dependent variable Rating and an independent variable Price.

ANOVA

df SS MS F

Regression 1 372.707 372.707 42.927

Residual 15 130.234 8.682

Total 16 502.941

Coefficients Standard Error t Stat P-value

Intercept 45.623 3.630 12.569 0.000

Price 0.107 0.016 6.552 0.000

a. Use the critical value approach to perform an F test for the significance of the linear relationship between Rating and Price at the 0.05 level of significance.

b. Calculate the coefficient of determination.

c. What percentage of the variability of Rating can be explained by its linear relationship with Price? What is the sample correlation coefficient?

d. What is the estimated regression equation?

e. Use the p-value approach to perform a t test for the significance of the linear relationship between Price and Rating at the 0.05 level of

significance.

The estimated regression equation for a model involving two independent variables and 65 observations is:

yhat = 55.17+1.2X1 -0.163X2

Other statistics produced for analysis include: SSR = 12370.8, SST = 35963.0,

Sb1 = 0.33, Sb2 = 0.20.

a. Interpret b1 and b2 in this estimated regression equation

b. Predict y when X1 = 65 and X2 = 70.

c. Compute R-square and Adjusted R-Square.

d. Comment on the goodness of fit of the model.

e. Compute MSR and MSE.

f. Compute F and use it to test whether the overall model is significant using

a p-value ( = 0.05).

g. Perform a t test using the critical value approach for the significance of 1.

Use a level of significance of 0.05.

h. Perform a t test using the critical value approach for the significance of 2.

Use a level of significance of 0.05.