11.Holding everything else constant, do men get paid more than women? Use a 5 percent level of significance. No, since the t-value:

A)   exceeds the critical value of 1.65.

B)   exceeds the critical value of 1.96.

C)   does not exceed the critical value of 1.96.

D)   does not exceed the critical value of 1.65.

12.A real estate agent wants to develop a model to predict the selling price of a home. The agent believes that the most important variables in determining the price of a house are its size (in square feet) and the number of bedrooms. Accordingly, he takes a random sample of 32 homes that has recently been sold. The results of the regression are:

	Coefficient	Standard Error	t-statistics
Intercept	66,500	59,292	1.12
House Size	74.30	21.11	3.52
Number of Bedrooms	10306	3230	3.19

 R² = 0.56; F = 40.73

What is the predicted price of a house that has 2,000 square feet of space and has 4 bedrooms?

A)   $114,432.

B)   $292,496.

C)   $292,496.

D)   $256,324.

13.What percent of the variability in the dependent variable is explained by the independent variable?

A)   40.73%.

B)   21.11%.

C)   56.00%.

D)   12.68%.

14.The model indicates that at the 5 percent level of significance:

A)   the slopes are significant but the constant is not.

B)   the slopes are not significant but the constant is.

C)   neither the slopes nor the constant are significant.

D)   the slopes and the constant are statistically significant.

15.When a number of independent variables in a multiple regression are highly correlated with each other, the problem is called:

A)   autocorrelation.

B)   multicollinearity.

C)   homoskedasticity.

D)   heteroskedasticity.

[此贴子已经被作者于2008-4-8 18:33:39编辑过]

11.Holding everything else constant, do men get paid more than women? Use a 5 percent level of significance. No, since the t-value:

A)   exceeds the critical value of 1.65.

B)   exceeds the critical value of 1.96.

C)   does not exceed the critical value of 1.96.

D)   does not exceed the critical value of 1.65.

The correct answer was D)

H_o: b_gender≤ 0
H_a b_gender > 0

t-value of 1.58 < 1.65 (critical value)

12.A real estate agent wants to develop a model to predict the selling price of a home. The agent believes that the most important variables in determining the price of a house are its size (in square feet) and the number of bedrooms. Accordingly, he takes a random sample of 32 homes that has recently been sold. The results of the regression are:

 R² = 0.56; F = 40.73

What is the predicted price of a house that has 2,000 square feet of space and has 4 bedrooms?

A)   $114,432.

B)   $292,496.

C)   $292,496.

D)   $256,324.

The correct answer was D)

66,500 + 74.30(2,000) + 10,306(4) = $256,324

13.What percent of the variability in the dependent variable is explained by the independent variable?

A)   40.73%.

B)   21.11%.

C)   56.00%.

D)   12.68%.

The correct answer was C)

R² = 0.56

14.The model indicates that at the 5 percent level of significance:

A)   the slopes are significant but the constant is not.

B)   the slopes are not significant but the constant is.

C)   neither the slopes nor the constant are significant.

D)   the slopes and the constant are statistically significant.

The correct answer was A)

DF = N-k-1 = 32-2-1 = 29. The t-critical value at 5% significance for a 2-tailed test with 29 df = 2.045. T-values for the slope coefficients are 3.52 and 3.19, which are both greater than 2.045. (critical value). For the constant, the t-value of 1.2 < 2.045.

15.When a number of independent variables in a multiple regression are highly correlated with each other, the problem is called:

A)   autocorrelation.

B)   multicollinearity.

C)   homoskedasticity.

D)   heteroskedasticity.

The correct answer was B)

Multicollinearity is present when the independent variables are highly correlated.