Pete Zaria would like to study the relationship between pizza sales and advertis

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Pete Zaria would like to study the relationship between pizza sales and advertising. The following is the result of a regression analysis Pete conducted for monthly sales of pizza and advertising (both in thousands of dollars)

SUMMARY OUTPUT Regression Statistics Multiple R 0.22208 R Square (5) Adjusted R Square 0.036297 Standard Error (4) Observations (3) ANOVA df SS MS F Significance F Regression 1 (2) 153.6546 3.787117 0.055498 Residual 73 (1) 40.57298 Total 74 3115.482 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 74.180 1.798983 41.23426 2.56E-52 70.59436 77.76509 ADVERT 1.733 (6) (7) 0.055498 (8) (9) How many many monthly sales and advertising data were used in the study? 73 74 75 77 The predicted sales when $2 (thousand) is spent on advertising is: $77.64 $79.97 $82.37 $84.84 The value for SSE in (1) is: 3124.662 3069.413 3015.140 2961.827 The variance of the prediction error is ______ 2298.8 40.57 82.1 9.06 The value for SSR in (2) is: 173.840 166.833 160.108 153.655 The value for the standard error of estimate se(e) in (4) is: 6.370 7.061 8.577 8.819 The value for R² in (5) is: 0.0266 0.0493 0.1702 0.2467 Given (x x)² = 51.1848, the value of the standard error of the slope coefficient in (6) is: 0.8903 1.0898 1.3339 1.6326 The value of the t stat |t| in (7) is: 2.992 2.413 1.946 1.755 The lower and upper end of a 95% confidence interval for the population slope parameter in (8) and (9), respectively, are: -0.042 3.507 0.050 3.598 0.211 3.759 0.237 3.785

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Pete Zaria would like to study the relationship between pizza sales and advertis

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