\begin{tabular}{|l|r|r|r|} \hline Market & Weekly Gross Revenue (S100s) & Television Advertising & Newspaper Advertising \\ \hline Mobile & 101.3 & 5.0 & 1.5 \\ \hline Shreveport & 51.9 & 3.0 & 3.0 \\ \hline Jackson & 74.8 & 4.0 & 1.5 \\ \hline Birmingham & 126.2 & 4.3 & 4.3 \\ \hline Little Rock & 137.8 & 3.6 & 4.0 \\ \hline Biloxi & 101.4 & 3.5 & 2.3 \\ \hline New Orleans & 237.8 & 5.0 & 8.4 \\ \hline Baton Rouge & 219.6 & 6.9 & 5.8 \\ \hline \end{tabular} DixieShowtime Theaters owns and operates several movie theaters in different markets. The owners would like to estimate weekly gross revenue as a function of advertising expenditures. Data for a sample of eight markets for a recent week is provided in the dataset. a. Develop an estimated regression equation with the amount of television advertising as the independent variable. Test for significant relationship between television advertising and weekly gross revenue at 0.05 level of significance. Is this relationship significant? b. How much of the variation in the sample values of weekly gross revenue does the model in part (a) explain? c. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. Which of the variables are significant? What are the interpretations of the regression parameters i.e. beta 1 and beta 2 ? d. Given the results in (a) and (c) which is the preferred model. Why