1. A measure of goodness of fit for the estimated regression equation is the  multiple coefficient of determination.
2. A measure of identifying the effect of an unusual x value on the regression results is called  leverage
3. A multiple regression model has the estimated form
   
   = 10 – 11x + 15w – 4q
   ​
   As x increases by 1 unit (holding w and q constant), y is expected to  decrease by 11 units
4. A multiple regression model has the following estimated form:
   
   = 4 – 6x + 8w
   
   As x increases by 1 unit (holding w constant), y is expected to  decrease by 6 units
5. A regression analysis involved 10 independent variables and 27 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have  16 degrees of freedom
6. A regression analysis involved 17 independent variables and 697 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have 679 degrees of freedom
7. A regression analysis involved 2 independent variables and 27 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have _____ degrees of freedom.  24
8. A regression analysis involved 5 independent variables and 99 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have _____ degrees of freedom.    93
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 – 4×1 + 5×2
   ​
   For this model, SSR = 3500, SSE = 1500, and the sample size is 20. The adjusted multiple coefficient of determination for this problem is   .6647
10. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
    ​
    = 8 – 4×1 + 5×2
    ​
    For this model, SSR = 3500, SSE = 1500, and the sample size is 20. The coefficient of x2 indicates that if television advertisement is increased by $1 (holding the unit price constant), sales are expected to   increase by $5,000
11. A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function:
    ​
    = 8 – 4×1 + 5×2
    ​
    For this model, SSR = 3500, SSE = 1500, and the sample size is 20. The coefficient of the unit price indicates that if the unit price is  increased by $1 (holding advertisement constant), sales are expected to decrease by $4000.
12. 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   130 degrees of freedom
13. A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares.
    SSR = 165SSE = 60
    ​
    The multiple coefficient of determination is   .7333
14. For a multiple regression model, SST = 1000 and SSR = 800. The multiple coefficient of determination is .8
15. For a multiple regression model, SST = 200 and SSE = 60. The multiple coefficient of determination is   7
16. If a categorical variable has k levels, the number of dummy variables required is   k-1
17. If an independent variable is added to a multiple regression model, the R2 value  ​becomes larger even if the variable added is not statistically significant.
18. In a multiple regression analysis involving 5 independent variables and 30 observations, SSR = 380 and SSE = 45. The multiple coefficient of determination is   .89
19. In a multiple regression analysis, SSR = 1000 and SSE = 200. The F statistic for this model is  not enough information
20. In a multiple regression analysis, SSR = 1000 and SSE = 200. The multiple coefficient of determination is  .83
21. In a multiple regression model involving 44 observations, the following estimated regression equation was obtained.
    ​
    = 50+ 13×1 + 40×2 + 68×3
    ​
    For this model, SSR = 600 and SSE = 300. MSR for this model is    200
22. In a multiple regression model involving 44 observations, the following estimated regression equation was obtained.
    ​
    = 50 + 13×1 + 40×2 + 68×3
    ​
    For this model, SSR = 600 and SSE = 400. The computed F statistic for testing the significance of the above model is    20
23. In a multiple regression model involving 44 observations, the following estimated regression equation was obtained:
    
    = 30 + 18×1 + 43×2 + 87×3
    ​
    What is bo?   30
24. In a multiple regression model involving 50 observations, the following estimated regression equation was obtained:
    ​
    = 20 + 5×1 – 4×2 + 8×3 + 8×4
    ​
    For this model, SSR = 700 and SSE = 100. The multiple coefficient of determination for the above model is  .875
25. In a multiple regression model involving 50 observations, the following estimated regression equation was obtained:
    ​
    = 20 + 5×1 – 4×2 + 8×3 + 8×4
    ​
    For this model, SSR = 700 and SSE = 100. The computed F statistic for testing the significance of the above model is   78.75
26. In a multiple regression model, the error term ε is assumed to  can be normally distributed
27. In a multiple regression model, the values of the error term ε are assumed to be  independent of each other
28. In logistic regression,   the dependent variable only assumes two discrete values.
29. In multiple regression analysis, the correlation among the independent variables is termed  multicollinearity
30. 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   3 and 43
31. In order to test for the significance of a regression model involving 5 independent variables and 36 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are   5 and 30
32. In order to test for the significance of a regression model involving 10 independent variables and 260 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are  10 and 429
33. The _______ of an observation is determined by how far the values of the independent variables are from their means.  leverage
34. The following estimated regression equation was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).
    ​
    = 30 + 0.7×1 + 3×2
    ​
    Also provided are SST = 1200 and SSE = 384. The yearly income (in $) expected of a 24-year-old female individual is  $49,800
35. The following estimated regression equation was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).
    ​
    = 30 + 0.7×1 + 3×2
    ​
    Also provided are SST = 1200 and SSE = 384. The test statistic for testing the significance of the model is  28.69
36. The interpretation of the coefficient of x1 is that   a one unit increase in x1 will lead to a 7.682 unit decrease in y when all other variables are held constant.
37. The mathematical equation that explains how the dependent variable y is related to several independent variables x1, x2, …, xp and the error term ε is a(n)   multiple regression model
38. The numerical value of the coefficient of determination    can be larger or smaller than the coefficient of correlation.
39. The sum of squares due to error (SSE) equals   6308.9
40. The test statistic used to determine if there is a relationship among the variables equals   5
41. We want to test whether the parameter β1 is significant. The test statistic equals  -2.9

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