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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?

Question

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?

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Solution

To find the critical value of F at the 5% level of significance, we need to know the degrees of freedom for the numerator and the denominator.

The degrees of freedom for the numerator (df1) is the number of variables added to the model, which is 1 (since we are adding X1 to the model that already includes X2).

The degrees of freedom for the denominator (df2) is the total number of observations minus the number of variables in the full model (including the constant term) which is 12 - 3 = 9.

So, we have df1 = 1 and df2 = 9.

Using an F-distribution table or an online F-distribution calculator, we can find that the critical value of F at the 5% level of significance for df1 = 1 and df2 = 9 is approximately 5.12.

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