13.23 This is all 1 question. The owner of Showtime Movie Theaters, Inc., would
ID: 3061233 • Letter: 1
Question
13.23
This is all 1 question.
The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Gross Televison Newspaper Revenue Advertising Advertising (*1000s) 96 90 96 92 95 94 95 94 ($1000s) (1000s) 1.5 1.5 3.5 3.3 3.3 5.2 2.5 2.5 3.5 2.5 a. Use a .01 to test the hypotheses Ha-a, and/or 2 is not equal to zero for the model y-A-1X1 + 2X2 + E, where television advertising ($1000s) x2newspaper advertising (S1000s) Compute the F test statistic (to 2 decimals). What is the p-value? What is your conclusion? b. Use a = .05 to test the significance of 1. Compute the t test statistic (to 2 decimals). What is the p-value? What is your conclusion? Should x1 be dropped from the model? C. Use a = .05 to test the significance of 2. Compute the t test statistic (to 2 decimals). What is the p-value? What is your conclusion? Should x2 be dropped from the model? Session TimeoutExplanation / Answer
Following is the output of multiple regression generated by excel:
(a)
The F test statistics is:
F = 56.25
The p-value is:
p-value = 0.0004
Since p-value is less than 0.05 so we reject the null hypothesis.
That is model is significant.
(b)
The test statistics is
t = 10.23
The p-value is:
p-value = 0.0002
Since p-value is less than 0.05 so we reject the null hypothesis.
No X1 should not dropped from the model.
(c)
The test statistics is
t = 5.92
The p-value is:
p-value = 0.0020
Since p-value is less than 0.05 so we reject the null hypothesis.
No X2 should not dropped from the model.
SUMMARY OUTPUT Regression Statistics Multiple R 0.978493903 R Square 0.957450318 Adjusted R Square 0.940430445 Standard Error 0.505270316 Observations 8 ANOVA df SS MS F Significance F Regression 2 28.72350954 14.36175477 56.2548456 0.000373457 Residual 5 1.276490462 0.255298092 Total 7 30 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 80.38131285 1.547910873 51.92890252 5.0065E-08 76.40228128 84.36034442 Television Advertising, X1 2.611260737 0.255332354 10.22690897 0.000153494 1.954908027 3.267613447 News paper advertising, X2 1.450780092 0.244971968 5.922229005 0.00195698 0.821059602 2.080500582Related Questions
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