Question

Case 3

In order to determine whether or not the number of automobiles sold per day (Y) is related to price (X₁ in $1,000), and the number of advertising spots (X₂), data were gathered for 7 days. Part of the regression results is shown below.

	Coefficient	Standard Error
Intercept	0.8051
X1	0.4977	0.4617
X2	0.4733	0.0387
Analysis of Variance
Source of	Degrees	Sum of	Mean
Variation	of Freedom	Squares	Square	F
Regression		40.700
Error		1.016

Refer to case 3. At a = 0.05, test to determine if the fitted equation developed in Part a represents a significant relationship between the independent variables and the dependent variable.

Conclusion is

Question 17 options:

	F = 80.12; p-value > .01; Don't reject H0 The model is not significant at alpha 0.05
	F = 8.12
	F = 80.12; p-value < .01 (almost zero); reject H0 and conclude that te model is significant at alpha 0.05
	None of these alternatives is correct.

Refer to case 3

At 95% confidence, test to see if price is a significant variable.

Use test statistics

Question 18 options:

	F
	t
	both t and F
	None of these alternatives is correct.

Refer to case 3. At 95% confidence, test to see if price is a significant variable.

Conclusion is

Question 19 options:

	t = 0.008; p-value less than alpha . Reject H0; price is a significant variable at alpha 0.05
	t = 1.078; p-value is between 0.1 and 0.2; do not reject H0; price is not a significant variable at 95% confidence.
	t = 1.078; p-value is less than 0.1 ; reject H0 price is a significant variable at 95% confidance
	None of these alternatives is correct.

Refer to case 3

Determine the multiple coefficient of determination

and interpret this number

Question 20 options:

	0.9756. 97.56% of the variation of the number of automobiles sold per day is explained by the variation in price and the number of advertising spots.
	0.9756 97.56% of the variation of the number of automobiles sold per day is explained by the variation in price.
	0.3467 34.67% of the variation of the number of automobiles sold per day is explained by the variation in price.
	0.7654 76.54% of the variation of the number of automobiles sold per day is explained by the variation in the number of advertising spots.

Answer 1

Solution: Here concept of Multiple linear regression is used.