Cascade Pharmaceuticals Company developed the following regression model, using 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 (× $1,000) for the cold remedy X2 = competitors' advertising for similar products (× $10,000) Here is additional information concerning the regression model: Sb1 = 0.052, sbg = 0.090, R² = 0.640, se = 1.63, F-statistic = 31.402, and Durbin-Watson (d) statistic = 0.499. Sb2 Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the cold remedy? (Hint: to.05/2,33-3=2.042.) Check all that apply. X1 X2 What proportion of the total variation in sales is explained by the regression equation? ○ 0.052 0.142 ○ 0.090 ○ 0.640 The given F-value shows that you, reject the null hypothesis that neither of the independent variables explains a significant (at the 0.05 level) proportion of the variation in income. (Hint: F0.05,2,33-2-1=3.316.)