Cascade Pharmaceuticals Company developed the following regression model, suing time series data from the past 33 quarters, for one of its nonprescription cold remedies: Y=-1.04+0.24X1-0.27X2 where Y=quarterly sales (in thousands of cases) of the cold remedy, X1=Cascade’s quarterly advertising (*$1000) for the cold remedy, X2 = competitors’ advertising for similar products (*$10,000) Here is additional information concerning the regression model: sb1=0.032, sb2=0.07, R2 =0.64, se=1.63, F-statistic=31.402, Durbin-Watson (d) statistic=.4995a. Which of the independent variables (if any) appear to be statistically significant (at the .05 level) in explaining sales of the cold remedy?b. What proportion of the total variation in sales is explained by the regression equation?c. Perform an F-test (at the .05 level) of the overall explanatory power of the model.d. How do the results in part (d) affect you answers to parts (a), (b), and (c)?e. What additional statistical information (if any) would you find useful in the evaluation of this model?