eBook Video Exerdise 15.15) ers, Inc., used multiple regression analysis to pred

Question

eBook Video Exerdise 15.15) ers, Inc., used multiple regression analysis to predict gross revenue () asa (x2). The estimated regression equation was Weekly Gross Televison Newspaper ($1000s) ($1000s) ($1000s) 2.5 97 90 95 92 96 95 95 2.5 2.5 4.3 2.3 4.2 2.5 2.5 4.5 3.5 y 85.11.53xs +1.11x The computer solution provided SST = 35.5 and SSR 34.772. a. Compute R2 and R2. (to 3 decimals). R 0.840 R0.800 b. When television advertising was the only independent variable, R2- 653 and R. .595. Are the multiple regress ter variability is explained when both independent variables are used toee to search

Explanation / Answer

The statistical software output for this problem is:

Multiple linear regression results:
Dependent Variable: y
Independent Variable(s): x1, x2
y = 85.071027 + 1.5252897 x1 + 1.1133842 x2

Parameter estimates:

Analysis of variance table for multiple regression model:

Summary of fit:
Root MSE: 0.38169772
R-squared: 0.9795
R-squared (adjusted): 0.9713

Hence,

R2 = 0.989

Ra2 = 0.971

Parameter Estimate Std. Err. Alternative DF T-Stat P-value Intercept 85.071027 0.64596839 0 5 131.69534 <0.0001 x1 1.5252897 0.11154534 0 5 13.674168 <0.0001 x2 1.1133842 0.16371656 0 5 6.8006812 0.001

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