# Question: Recall from Exercise 14 5 that Enterprise Industries has observed the

y = β0 + β1x1 + β2x2 + β3x3 + β4DB + β5DC + ε
a. Because this model does not use a dummy variable to represent advertising campaign A, the parameter β4 represents the effect on mean demand of advertising campaign B compared to advertising campaign A, and the parameter β5 represents the effect on mean demand of advertising campaign C compared to advertising campaign A. (1) Use the regression output to find and report a point estimate of each of the above effects and to test the significance of each of the above effects. (2) Find and report a 95 percent confidence interval for each of the above effects. (3) Interpret your results.
b. The prediction results at the bottom of the output correspond to a future period when Fresh’s price will be x1 = 3.70, the average price of similar detergents will be x2 = 3.90, Fresh’s advertising expenditure will be x3 6.50, and advertising campaign C will be used. (1) Show (within rounding) how 8.61621 is calculated. (2) Find, report, and interpret a 95 percent confidence interval for mean demand and a 95 percent prediction interval for an individual demand when x1 = 3.70, x2 = 3.90, x3 = 6.50, and campaign C is used.
c. Consider the alternative model
y = β0 + β1x1 + β2x2 + β3x3 + β4DA + β5DC = ε
Here DA equals 1 if advertising campaign A is used and equals 0 otherwise. Because this model does not use a dummy variable to represent advertising campaign B, the parameter β5 in this model represents the effect on mean demand of advertising campaign C compared to advertising campaign B. The Excel output of the least squares point estimates of the parameters of the alternative model are as follows.
Use the Excel output to (1) test the significance of the effect represented by β5 and (2) find a 95 percent confidence interval for b β5. (3) Interpret your results.

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