SUMMARY OUTPUT 0.377 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.020 9 ANOVA df SS MS F Significance F 33.333 Regression Residual Total 200.889 Intercept Advertising Coefficients Standard Error t Stat P-value 19.889 6.438 3.089 0.018 1.667 1.546 Lower 95% 4.664 -1.990 Upper 95% Lower 95.0% Upper 95.0% 35.113 4.664 35.113 5.323 -1.990 5.323 QUESTION 5 Compute the t-test statistic to test the significance of the linear relationship. 1.078 O 0.927 0 3.873 4.823 QUESTION 6 At a = 0.05, we conclude that there is a significant linear relationship between weekly sales and advertising expenditures. True False SUMMARY OUTPUT 0.377 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.020 9 ANOVA df SS MS F Significance F 33.333 Regression Residual Total 200.889 Intercept Advertising Coefficients Standard Error t Stat P-value 19.889 6.438 3.089 0.018 1.667 1.546 Lower 95% 4.664 -1.990 Upper 95% Lower 95.0% Upper 95.0% 35.113 4.664 35.113 5.323 -1.990 5.323 QUESTION 5 Compute the t-test statistic to test the significance of the linear relationship. 1.078 O 0.927 0 3.873 4.823 QUESTION 6 At a = 0.05, we conclude that there is a significant linear relationship between weekly sales and advertising expenditures. True False