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The value of R-square indicates the amounts of variation in the dependent variable that is describeed by the independent variable

You have been provided with the following regression output. The dependent variable is unit sales of a product, and the independent variable is the dollar value of newspaper advertising for that product. The unit of analysis is weeks; that is, each of the observations in the underlying sample data represents a separate week of sales and newspaper advertising.
Regression Analysis: Sales versus Newspaper
The regression equation is
Sales = 6514 + 0.0386 Newspaper

Predictors

   Co-eff

           SECo-eff           

          T              

           P

Constant

   6514

         1138

     5.72

         0.000

Newspaper      

   0.038625                     

      0.005494

     7.03

         0.00

S = 5630.70   R-Sq = 24.3%   R-Sq(adj) = 23.8%

Analysis of Variance

Source

      D F

           S S                      

        M S                        

 F

 P

Regression  

      1

       1567134272

      1567134272

 49.43

 0.000

Residual Error

      154

       4882532724

      31704758

 

 

Total      

      155

       6449666996

 

 

 

 

How much variability would you have if you predict sales with this model?

What would be your best point estimate for average Sales in weeks for which Newspaper advertising were $1 million? What would be a suitable interval estimate for this? (Use 95% limits.)

Statistics and Probability, Statistics

  • Category:- Statistics and Probability
  • Reference No.:- M921064

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