Linear Regression-The owner wishes to build a model relating

Subject: Mathematics / Statistics
Question
Linear Regression
The owner wishes to build a model relating revenues to advertising expenditures into three categories TV, newspaper, and direct mail advertising.

Regression statistics

Multiple R 0.967

R square. 0.94

Adjusted R square 0.887

Standard Error 0.64

Observations. 8

ANOVA. df. SS. MS. F. Significance F

Regression. 3. 23.85. 7.95. 19.23. 0.0072

Residual. 4. 1.65. 0.413

Total. 7. 25.5

Standard error. t test. F value. Lower 95. Upper 95

Coefficients Intercept 73.93. 4.53 16.34. 0.00008. 61.37. 86.5

TV. 2.38. 0.32. 7.49. 0.0017. 1.5. 3.27

Newspaper. 1.45. 0.356. 4.09. 0.015. 0.467. 2.44

Mail. 1.82. 0.2777. 6.57. 0.0028. 1.05. 2.58

Which statement below best describes the goodness of fit?

A) the data is a good fit because s= 64 meaning 64% of the charge in revenue is explained

B) data is a good fit because F value is 0.0077

C) approximately 88% of the change in revenues can be explained by the three independent variables in the model

D) data is a good fit because r= 0.96

Which independent variable is the least significant in this regression relationship?

A) the number of newspaper odds

B) direct mai advertising because the p value is 0.0028

C) direct mail because the t-test is 6.57

D) the number of TV ads