Quantitative predictor variables are entered into a regression model through indicator variables. ...

Quantitative predictor variables are entered into a regression model through indicator variables.
  Indicate whether the statement is true or false

Q. 2

Qualitative predictor variables are entered into a regression model through dummy variables.
  Indicate whether the statement is true or false

Q. 3

Which of the following methods is used to help assess whether the regression model meets the assumption of having normally distributed residuals?
 a. Develop a normal probability plot of the residuals.
  b. Develop a histogram of the residuals.
  c. Develop a normal probability plot of the population means.
  d. Both develop a normal probability plot of the residuals and develop a histogram of the residuals.
  e. Neither develop a normal probability plot of the residuals nor develop a histogram of the residuals.

Q. 4

In a multiple regression model, if the residuals have a constant variance, which of the following should be evident?
 a. The residual mean should be close to zero and the residual standard deviation should be close to 1.0.
  b. The plot of residuals against each independent variable should show that the spread in the residuals is about the same at all levels of the independent variables.
  c. The residuals should have a variance equal to zero for all levels of the independent variable.
  d. All of these.
  e. None of these.

Q. 5

In a multiple regression model, which of the following statements is false?
 a. The coefficient of determination will be equal to the square of the largest correlation value between the dependent variable and the independent variables.
  b. The mean of the residuals is equal to the variance of all combinations of levels of the independent variables.
  c. Adding more independent variables that have a low correlation with the dependent variable will decrease the value of the coefficient of multiple determination.
  d. All of these.
  e. None of these.

Q. 6

A multiple regression equation includes 5 independent variables, and the coefficient of determination is 0.81 . The percentage of the variation in y that is explained by the regression equation is:
 a. 81
  b. 90
  c. 86
  d. 85
  e. about 16

Q. 7

In multiple regression analysis involving 10 independent variables and 100 observations, the critical value of t for testing individual coefficients in the model will have:
 a. 100 degrees of freedom
  b. 10 degrees of freedom
  c. 99 degrees of freedom
  d. 89 degrees of freedom
  e. 9 degrees of freedom

Q. 8

In testing the validity of a multiple regression model involving 10 independent variables and 100 observations, the numerator and denominator degrees of freedom for the critical value of F will be, respectively,
 a. 9 and 90
  b. 10 and 100
  c. 9 and 10
  d. 10 and 89
  e. 8 and 16

Q. 9

A multiple regression analysis involving three independent variables and 25 data points results in a value of 0.769 for the unadjusted multiple coefficient of determination. Then, the adjusted multiple coefficient of determination is:
 a. 0.385
  b. 0.877
  c. 0.591
  d. 0.736
  e. 0.819