Regression Analysis r 0.762 R 0.873 Std. Error 11.547 n 7 k 1 Dep. Var. Sales...

 

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Regression Analysis r 0.762 R 0.873 Std. Error 11.547 n 7 k 1 Dep. Var. Sales ANOVA df 1 2,133.3333 133.3333 F 16.00 P-value 0103 Source SS MS Regression 2,133.3333 Residual Total 2,800.0000 666.6667 Regression output Variables Coefficients std. error Intercept Advertising Confidence interval t (df 5) p-value 95% lower 95% upper 42.8505 83.8162 63.3333 6.6667 7.9682 0005 0103 7.948 1.6667 4.000 The local grocery store wants to predict its daily sales in dollars. The manager believes that the amount of newspaper advertising significantly affects sales. He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars) and advertising expenditures (in thousands of dollars). The Excel/MegaStat output given above summarizes the results of the regression model. What is the estimated simple linear regression equation? Regression Analysis r 0.762 R 0.873 Std. Error 11.547 n 7 k 1 Dep. Var. Sales ANOVA df 1 2,133.3333 133.3333 F 16.00 P-value 0103 Source SS MS Regression 2,133.3333 Residual Total 2,800.0000 666.6667 Regression output Variables Coefficients std. error Intercept Advertising Confidence interval t (df 5) p-value 95% lower 95% upper 42.8505 83.8162 63.3333 6.6667 7.9682 0005 0103 7.948 1.6667 4.000 The local grocery store wants to predict its daily sales in dollars. The manager believes that the amount of newspaper advertising significantly affects sales. He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars) and advertising expenditures (in thousands of dollars). The Excel/MegaStat output given above summarizes the results of the regression model. What is the estimated simple linear regression equation?

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The simple linear regression equation can be written from the Excel output of ... View the full answer