Question

6. In the simple linear regression model, the y-intercept represents the: a. change in y per unit change in x. b. change in x per unit change in y. c. value of y when x = 0. d. value of x when y = 0. 7. In the simple linear regression model, the slope represents the: a. value of y when x = 0. b. average change in y per unit change in x. c. value of x when y = 0. d. average change in x per unit change in y. 8. In regression analysis, the residuals represent the: a. difference between the actual y values and their predicted values. b. difference between the actual x values and their predicted values. c. square root of the slope of the regression line. d. change in y per unit change in x. 9. The least squares method for determining the best fit minimizes: a. total variation in the dependent variable b. sum of squares for error c. sum of squares for regression d. All of these choices are true. 10. A regression analysis between sales (in $1000) and advertising (in $100) resulted in the following least squares line: ? = 75 + 6x. This implies that if advertising is $800, then the predicted amount of sales (in dollars) is: a. $4875 b. $123,000 c. $487,500 d. $12,300

          6. In the simple linear regression model, the y-intercept represents the:
a. change in y per unit change in x.
b. change in x per unit change in y.
c. value of y when x = 0.
d. value of x when y = 0.

7. In the simple linear regression model, the slope represents the:
a. value of y when x = 0.
b. average change in y per unit change in x.
c. value of x when y = 0.
d. average change in x per unit change in y.

8. In regression analysis, the residuals represent the:
a. difference between the actual y values and their predicted values.
b. difference between the actual x values and their predicted values.
c. square root of the slope of the regression line.
d. change in y per unit change in x.

9. The least squares method for determining the best fit minimizes:
a. total variation in the dependent variable
b. sum of squares for error
c. sum of squares for regression
d. All of these choices are true.

10. A regression analysis between sales (in $1000) and advertising (in $100) resulted in
the following least squares line: ? = 75 + 6x. This implies that if advertising is $800, then
the predicted amount of sales (in dollars) is:
a. $4875
b. $123,000
c. $487,500
d. $12,300

6. In the simple linear regression model, the y-intercept represents the:
a. change in y per unit change in x.
b. change in x per unit change in y.
c. value of y when x = 0.
d. value of x when y = 0.

7. In the simple linear regression model, the slope represents the:
a. value of y when x = 0.
b. average change in y per unit change in x.
c. value of x when y = 0.
d. average change in x per unit change in y.

8. In regression analysis, the residuals represent the:
a. difference between the actual y values and their predicted values.
b. difference between the actual x values and their predicted values.
c. square root of the slope of the regression line.
d. change in y per unit change in x.

9. The least squares method for determining the best fit minimizes:
a. total variation in the dependent variable
b. sum of squares for error
c. sum of squares for regression
d. All of these choices are true.

10. A regression analysis between sales (in 1000) and advertising (in100) resulted in
the following least squares line: ? = 75 + 6x. This implies that if advertising is 800, then
the predicted amount of sales (in dollars) is:
a.4875
b. 123,000
c.487,500
d. 12,300

Added by Allen W.

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