Applied Statistics From Bivariate Through Multivariate Techniques 2nd Edition By Warner – Test Bank

Chapter 11: Multiple Regression with Two Predictor Variables

Multiple Choice

1. Which of the following is not a reason for using two predictors in a regression model:
a. determine if the two predictors together can account for a significant proportion of variance in Y.
b. determine if one of the predictors is a suppressor variable.
c. compare which of the two predictors has a stronger relationship with Y.
d. find the amount of shared or explained variance between the predictors when controlling for Y.
Ans: d

2. The notation rY(1.2) is the:
a. partial correlation between Y and X1.
b. semipartial correlation between Y and X1.
c. part-whole correlation between Y and X1.
d. bivariate correlation between Y and X1.
Ans: b

3. Which value represents the proportion of variance in Y uniquely predictable from X2 when X1 is partialled out:
a. sr21
b. sr22
c. R2Y.12
d. 1 – R2Y1.2
Ans: b

4. Which value represents the proportion of variance in Y predictable from X1 and X2 combined:
a. sr21
b. sr22
c. R2Y.12
d. 1 – R2Y1.2
Ans: c

5. Which notation represents the null hypothesis, do X1 and X2 combined predict Y:
a. H0: R(Y1.2 ) = 0
b. H0: RY.12 = 0
c. H0: R(Y.12 ) = 0
d. H0: RY2.1 = 0
Ans: b

6. Given Y’ = b0 + b1X1 + b2X2, the partial slope b1 is interpreted as:
a. for each one-unit increase in X1, there is a b1 change in Y’ controlling for X2.
b. for each one-unit increase in X1, there is a b0 + b1 change in Y’ controlling for X2.
c. for each one-unit increase in X1, there is a b1 + b2 change in Y’.
d. for each one-unit increase in Y’, there is a b0 + b1 change in X1 controlling for X2.
Ans: a

7. Which is not an assumption for a linear regression with two predictors:
a. Y should be categorical or quantitative.
b. X1 and X2 should be categorical or quantitative.
c. there should be no interaction between X1 and X2.
d. the variance in Y should be homogenous across levels of X1 and X2.
Ans: a

8. Which is true for the semipartial correlation ry(1.2) :
a. the variance of X1 has been removed from X2 but not its variance with Y.
b. the variance of X1 has been removed from both X2 and Y.
c. the variance of X2 has been removed from X1 but not its variance with Y.
d. the variance of X1 has been removed from both X2 and Y.
Ans: c

9. For regression with two predictors, which test statistic evaluates the null hypothesis H0 :R = 0:
a. F
b. t
c. q
d. b
Ans: a

10. For regression with two predictors, which test statistic evaluates the null hypothesis H0 :R = 0:
a. F
b. t
c. q
d. b
Ans: b

11. Which is not a component of variance that can be determined for regression with two predictors:
a. the proportion of variance that is uniquely predictable from X1.
b. the proportion of variance that is uniquely predictable from X2.
c. the proportion of unexplained variance in X1.
d. the proportion of variance in Y that cannot be predicted from either X1 or X2.
Ans: c