Question

A marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage industry and collects monthly data for 25 firms. He estimates the model: Sales = β0 + β1 Advertising + ε. The following ANOVA table shows a portion of the regression results. df SS MS F Regression 1 78.53 78.53 3.58 Residual 23 504.02 21.91 Total 24 582.55 Coefficients Standard Error t-stat p-value Intercept 40.10 14.08 2.848 0.0052 Advertising 2.88 1.52 -1.895 0.0608 Which of the following is true? A) If Advertising goes up by $100, then we predict Sales to go up by $2,880. B) If Sales go up by $100, then we predict Advertising to go up by $2,880. C) If Advertising goes up by $100, then we predict Sales to go up by $4,298. D) If Sales go up by $100, then we predict Advertising to go up by $4,298.

          A marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage industry and collects monthly data for 25 firms. He estimates the model: Sales = β0 + β1 Advertising + ε.

The following ANOVA table shows a portion of the regression results.

df SS MS F
Regression 1 78.53 78.53 3.58
Residual 23 504.02 21.91
Total 24 582.55

Coefficients Standard Error t-stat p-value
Intercept 40.10 14.08 2.848 0.0052
Advertising 2.88 1.52 -1.895 0.0608

Which of the following is true?
A) If Advertising goes up by $100, then we predict Sales to go up by $2,880.
B) If Sales go up by $100, then we predict Advertising to go up by $2,880.
C) If Advertising goes up by $100, then we predict Sales to go up by $4,298.
D) If Sales go up by $100, then we predict Advertising to go up by $4,298.

Added by Breanna A.

Question

Please give Ace some feedback