8. Develop the equation of the simple regression line to predict sales from advertising expenditures, and find the correlation coefficient using these data, and test the positive significant of the slope of the regression line. Use a=0.05 and use only t test. Advertising (X) 12.5 3.7 21.6 60.0 37.6 6.1 16.8 41.2 11.3 Sales (Y) 148 55 338 994 541 89 126 379 145 SUMMARY OUTPUT Regression Statistics Multiple R 0.949779 R Square 0.90208 Adjusted R Square 0.888092 Standard Error 100.906 Observations 9 ANOVA df Significanc ef 8.9E-05 1 Regression Residual Total SS MS F 656609.4 656609.4 64.48714 71274.15 10182.02 727883.6 7 8 Coefficient $ Standard Error 55.55346 Stat P-value -0.76099 0.471517 Upper Lower 95% 9596 -173.638 89,08765 Lower Upper 95.0% 95.0% -173.63889.08765 -42.2754 Intercept Advertising 15.15882 1.887682 8.030388 8.9E-05 10.69516 19.62248 10.69516 19.62248 (A). Find the equation of the regression line: (B). Calculate the correlation coefficient r, and make a conclusion about how it is negative positive and define the strength of the correlation. (C). Test of significance: Steps: (1) Identify H. H (2) a=0.05 n d.r. (3) Find the critical value(s): (4) Identify the rejection region(s): (5) Find the standardized test statistic: Make decision: Interpret the decision in the context of the original claim. 8. Develop the equation of the simple regression line to predict sales from advertising expenditures, and find the correlation coefficient using these data, and test the positive significant of the slope of the regression line. Use a=0.05 and use only t test. Advertising (X) 12.5 3.7 21.6 60.0 37.6 6.1 16.8 41.2 11.3 Sales (Y) 148 55 338 994 541 89 126 379 145 SUMMARY OUTPUT Regression Statistics Multiple R 0.949779 R Square 0.90208 Adjusted R Square 0.888092 Standard Error 100.906 Observations 9 ANOVA df Significanc ef 8.9E-05 1 Regression Residual Total SS MS F 656609.4 656609.4 64.48714 71274.15 10182.02 727883.6 7 8 Coefficient $ Standard Error 55.55346 Stat P-value -0.76099 0.471517 Upper Lower 95% 9596 -173.638 89,08765 Lower Upper 95.0% 95.0% -173.63889.08765 -42.2754 Intercept Advertising 15.15882 1.887682 8.030388 8.9E-05 10.69516 19.62248 10.69516 19.62248 (A). Find the equation of the regression line: (B). Calculate the correlation coefficient r, and make a conclusion about how it is negative positive and define the strength of the correlation. (C). Test of significance: Steps: (1) Identify H. H (2) a=0.05 n d.r. (3) Find the critical value(s): (4) Identify the rejection region(s): (5) Find the standardized test statistic: Make decision: Interpret the decision in the context of the original claim
