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## Statistics

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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