A sample of 12 observations collected in a multiple regression study on two independent variables (X1 and X2) shows the following partial results. SST = 12321 and SSE = 3516. If SSR(X1) = 4496 and SSR(X2) = 5378, what would be the value of the partial F test statistic used to test the null hypothesis that variable X1 does not significantly improve the model after variable X2 has been included? Round your final answer to two decimal places.

A sample of 12 observations collected in a multiple regression study on two independent variables (X1 and X2) shows the following partial results. SST = 12321 and SSE = 3516. If SSR(X1) = 4496 and SSR(X2) = 5378, and you would like to test the null hypothesis that variable X1 does not significantly improve the model after variable X2 has been included, what would be the critical value of F at the 5% level of significance?

A sample of 12 observations collected in a multiple regression study on two independent variables (X1 and X2) shows the following partial results. SST = 12321 and SSE = 3516. If SSR(X1) = 4496 and SSR(X2) = 5378, what conclusion should be reached (at the 1% level of significance) when testing the null hypothesis that variable X2 does not significantly improve the model after variable X1 has been included? a. There is sufficient evidence at the 1% level of significance to conclude that variable X2 significantly improves the model after variable X1 has been included. b. There is insufficient evidence at the 5% level of significance to conclude that variable X1 significantly improves the model after variable X2 has been included. c. There is insufficient evidence at the 1% level of significance to conclude that variable X2 significantly improves the model after variable X1 has been included. d. There is sufficient evidence at the 1% level of significance to conclude that variable X1 significantly improves the model after variable X2 has been included.

A multiple regression has a sample of 16 with 3 independent variables. Given SSE = 180 and SSR = 90 what is the value of the F test statistic used to test the significance of the overall multiple regression model.

The overall regression F-statistic tests the null hypothesis that: a. all slope coefficients and the intercept are zero. b. all slope coefficients are zero. c. the slope coefficient of the variable of interest is zero, but that the other slope coefficients are not. d. the intercept in the regression and at least one, but not all, of the slope coefficients is zero.

Suppose that in a multiple regression the F test statistic is significant, but none of the t test statistics are significant. This means that ________. a. multicollinearity may be present b. autocorrelation may be present c. collinearity may be present d. (a) and (c).