1. A multiple regression model has A. more than one independent variable
2. A multiple regression model has the estimated form
= 5 + 6x + 7w
As x increases by 1 unit (holding w constant), y is expected to A. increase by 6 units
3. A multiple regression model has the estimated form
= 7 + 2×1 + 9×2
As x1 increases by 1 unit (holding x2 constant), y is expected to A. increase by 2 units
4. A regression analysis involved 8 independent variables and 99 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have A. 90 degrees of freedom.
5. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
= 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The coefficient of the unit price indicates that if the unit price is A. increased by $1 (holding advertisement constant), sales are expected to decrease by $3000
6. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
= 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The coefficient of x2 indicates that if television advertisement is increased by $1 (holding the unit price constant), sales are expected to A. increase by $5000.
7. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
= 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18. To test for the significance of the model, the test statistic F is A. 17.5
8. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
= 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18. To test for the significance of the model, the p-value is A. less than .01
9. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
= 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The adjusted multiple coefficient of determination for this problem is A. 66
10. A regression model involved 5 independent variables and 136 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have A. 130 degrees of freedom
11. A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical independent variables in a regression model is called A. a dummy variable.
12. In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The multiple coefficient of determination is A. .700
13. In a multiple regression analysis, SSR = 1000 and SSE = 200. The F statistic for this model is A. Not enough information is provided to answer this question
14. In a multiple regression model involving 44 observations, the following estimated regression equation was obtained.
= 29 + 18×1 + 43×2 + 87×3
For this model, SSR = 600 and SSE = 400. The computed F statistic for testing the significance of the above model is A. 20.00
15. In a regression model involving more than one independent variable, which of the following tests must be used in order to determine if the relationship between the dependent variable and the set of independent variables is significant? A. F test
16. In multiple regression analysis, A. there can be several independent variables, but only one dependent variable.
17. In order to test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are A. 3 and 43
18. In order to test for the significance of a regression model involving 14 independent variables and 255 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are A. 14 and 240
19. In order 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
20. The multiple coefficient of determination is A. SSR/SST
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