MGT3002 Week 3 Discussion

1. To test for the significance of a regression model involving 8 independent variables and 121 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are _____.

a. 8 and 112

b. 7 and 112

c. 8 and 121

d. 7 and 120

2. The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is called _____.

a. the standard error

b. a residual

c. a prediction interval

d. the variance

3. If the coefficient of determination is .81, then the coefficient of correlation _____.

a. must be 0.9

b. is .6561

c. must be positive

d. None of these answers are correct.

4. In a multiple regression model, the variance of the error term ε is assumed to be _____.

a. the same for all values of the dependent variable

b. −1

c. 0

d. the same for all values of the independent variable

5. A regression model between sales (y in $1000s), unit price (x1 in dollars) and television advertisement (x2 in dollars) resulted in the following function:

ŷ = 7 − 3x1 + 5x2

For this model, SSR = 3500, SSE = 1500, and the sample size is 18.

If we want to test for the significance of the regression model, the critical value of F at 95% confidence is _____.

a. 3.29

b. 4.54

c. 3.68

d. 3.24

6. In a regression model involving 44 observations, the following estimated regression equation was obtained:

ŷ = 29 + 18x1 + 43x2 + 87x3

For this model, SSR = 600 and SSE = 400.

The computed F statistic for testing the significance of the above model is _____.

a. .600

b. 1.500

c. 20.00

d. .6667

7. In multiple regression analysis, ______.

a. there must be only one independent variable

b. there can be any number of dependent variables but only one independent variable

c. the coefficient of determination must be larger than 1

d. there can be several independent variables, but only one dependent variable

8. The equation that describes how the dependent variable (y) is related to the independent variable (x) is called _____.

a. the correlation model

b. correlation analysis

c. the regression model

d. None of these answers are correct.

9. The interval estimate of the mean value of y for a given value of x is the _____.

a. correlation interval

b. prediction interval

c. confidence interval

d. residual interval

10. The numerical value of the coefficient of determination ______.

a. is always larger than the coefficient of correlation

b. can be larger or smaller than the coefficient of correlation

c. is negative if the coefficient of determination is negative

d. is always smaller than the coefficient of correlation

11. Below you are given a partial Excel output based on a sample of 16 observations.

ANOVA

df		SS	MS	F
Regression			4,853		2,426.5
Residual					485.3

Coefficients	Standard Error
Intercept	12.924		4.425
x1	-3.682		2.630
x2	45.216		12.560

The sum of squares due to error (SSE) equals _____.

a. 6,308.9

b. 4,853

c. 37.33

d. 485.3

12. A regression model involving 4 independent variables and a sample of 15 periods resulted in the following sum of squares:

SSR = 165

SSE = 60

The coefficient of determination is _____.

a. .7333

b. .5

c. .3636

d. .275

13. A regression model between sales (y in $1000s), unit price (x1 in dollars) and television advertisement (x2 in dollars) resulted in the following function:

ŷ = 7 − 3x1 + 5x2

For this model, SSR = 3500, SSE = 1500, and the sample size is 18.

If SSR = 600 and SSE = 300, the test statistic F is _____.

a. 17.5

b. 2.33

c. .70

d. 1.75

14. In regression analysis, the response variable is the _____.

a. dependent variable

b. intercept

c. slope of the regression function

d. independent variable

15. In a regression analysis, if SSE = 200 and SSR = 300, then the coefficient of determination is _____.

a. .600

b. 1.500

c. .400

d. .667