Chapter 19 Test Items

1. Tika has found that her sum of squares regression = 80 and her sum of squares residual = 10. What is her R value?

a. 7200

b. .72

c. .94

d. .80

2. Fatima was writing her results section in an article on organizational coaching and reported the following multiple linear regression result: “A multiple linear regression was utilized using the three domains of organizational coaching (affective, behavioral, and cognitive) as the

independent variables and job satisfaction as the dependent variable. The linear combination of the independent variables was significantly related to the degree to which a participant was satisfied with her or his job: F(3, 369) = 61.51, p < .0005. The sample multiple correlation coefficient, R, was .58, which indicates that approximately 34% of the variance of an individual’s motivation at work could be accounted for by the linear combination of the independent variables. However, only cognitive coaching (t = 3.33, p < .005, β = .27) and affective coaching (t = 4.39, p < .0005, β = .29) accounted for any of the unique variance.” Which of the following statements is false?

a. The linear combination accounted for 33% of the variance.

b. R2 = .3364

c. The multiple linear regression was statistically significant.

d. All three organizational coaching variables accounted for unique variance.

3. If Darlene finds that R2 = .81, what is her R value?

a. 9

b. .81

c. 81

d. .9

4. While calculating her regression, Polly finds that her sum of squares regression = 25 and her sum of squares total = 5. What is her R2 value?

a. 25

b. 5

c. 20

d. .25

5. If you have multiple interval/ratio variables and you want to determine if they account for unique variance in a single interval/ratio variable, which is the most appropriate test to conduct?

a. one-way ANOVA

b. correlations

c. simple linear regression

d. multiple linear regression

6. The regression test is part of which family of statistical tests?

a. general linear model family

b. general variance model family

c. general relationship model family

d. general regression model family

7. Which of the following is NOT a basic assumption of regression?

a. Both the independent variable(s) and dependent variable should be interval.

b. The sample need not be random.

c. Scores for each variable being compared must be obtained from each participant.

d. The cases represent scores that are independent of each other from one participant in your sample to the next participant.

8. Rory is researching how much variance in an individual’s heart rate changes when giving an impromptu speech as predicted by an individual’s level of communication apprehension. Rory gets a coefficient of determination R2. of .821. What does this mean?

a. 9% of the variance in an individual’s heart rate changes when giving an impromptu speech as predicted by an individual’s level of communication apprehension

b. 17.9% of the variance in an individual’s heart rate changes when giving an impromptu speech as predicted by an individual’s level of communication apprehension

c. 82% of the variance in an individual’s heart rate changes when giving an impromptu speech as predicted by an individual’s level of communication apprehension

d. 80% of the variance in an individual’s heart rate changes when giving an impromptu speech

as predicted by an individual’s level of communication apprehension

9. Which of the following is a mathematical adjustment to R2 that attempts to more accurately reflect the goodness of fit in the overall linear regression?

a. adjusted R2

b. R2

c. critical value

d. sum or squares

10. Which of the following indicates the difference between correlations and regression?

a. Correlation utilizes nominal variables, and regression does not.

b. Regression utilizes nominal variables, and correlation does not.

c. Correlation allows for analysis of multiple variables, and regression does not.

d. Correlation does not require that one knows which variable is dependent or independent, and regression does require specificity of independent and dependent variables.

For questions 11 to 17, use the regression results presented below. The independent variables in this study were willingness to communicate, communication apprehension, nonverbal immediacy, and communication competence. The dependent variable was body dysmorphia, a disorder where a person is unhealthily preoccupied with one's physical appearance or specific aspects of one's physical appearance.

11. In the multiple linear regression presented, what was the N?

a. 199

b. 195

c. 4

d. 400

12. In the multiple linear regression presented, what is the calculated R value for the multiple linear regression?

a. .34

b. .121

c. .103

d. 6.21

13. In the multiple linear regression presented, what was the calculated p value for the multiple linear regression?

a. p < .001

b. p = .00

c. p > .05

d. p < .0005

14. In the multiple linear regression presented, which of the following statements is correct?

a. The multiple linear regression was statistically significant.

b. The multiple linear regression was not statistically significant.

c. The multiple linear regression reported a large effect size.

d. The multiple linear regression reported a small effect size.

15. In the multiple linear regression presented, what was the variance accounted for by the regression model?

a. 12%

b. .10%

c. 90%

d. .09%

16. In the multiple linear regression presented, which variable(s) account for unique variance?

a. communication apprehension

b. willingness to communicate

c. communication competence

d. all accounted for unique variance

17. In the multiple linear regression presented, which of the following accurately represents the coefficient information for communication apprehension?

a. (t = 4.71, p < .001, ß = .37)

b. (t = –4.08, p > .05, ß = –.20)

c. (t = 24.85, p < .001, ß = .30)

d. (t = 4.08, p < .001, ß = .20)

18. What combination of variables do you need to have to calculate a multiple linear regression?

a. 2 or more interval/ratio independent variables, 1 interval/ratio dependent variable

b. 2 or more interval/ratio independent variables, 2 interval/ratio dependent variables

c. 1 interval/ratio independent variable, 1 interval/ratio dependent variable

d. 1 interval/ratio independent variable, 2 or more interval/ratio dependent variables

19. The typical formula associated with a regression is Y = mx + b. What is this formula for?

a. line

b. curve

c. variance accounted for

d. R

20. Samantha calculated a multiple linear regression. She found an R value of .25. How much variance is she accounting for?

a. 5%

b. 25%

c. .05%

d. .25%

21. The adjusted R2 is a more accurate portrayal of the variance accounted for.

a. True

b. False

22. A simple linear regression allows researchers to determine how a number of independent variables collectively account for variance in a single dependent variable.

a. True

b. False

23. When conducting a regression, scores for only the independent variable must be obtained from each participant.

a. True

b. False

24. The standard error of estimate provides a measure of how accurately the regression equation predicts independent variable values.

a. True

b. False

25. If R2 = .821, 25% of the variance in the dependent variable cannot be predicted by the independent variable(s).

a. True

b. False

26. When conducting a regression, cases must represent scores that are independent of each other from one participant to the next participant.

a. True

b. False

27. When conducting a regression, the population variances of the dependent variable are different for all levels of the independent variable.

a. True

b. False

Essays:

28. Explain the difference between correlation and regression.

29. Explain the purposes of linear regression.

30. Explain the purposes of multiple linear regression.

31. Interpret the results of the regression that are provided below. This study examined the relationships between stereotypes of flight attendants, ethnocentrism, and homonegative and the belief that all flight attendants should be female.

Matching:

32. Match each of the following terms with the correct statement.

a. R² = Indicates what proportion of the variability in a dependent variable can be predicted by its relationship with an independent variable(s).

b. General Linear Model = Regression is a member of this family of statistics.

c. Partial Regression Coefficient = Value in a multiple linear regression that helps explain the degree to which a dependent variable takes varying values and can be interpreted as a correlation.