1. Psy302 Quantitative Methods
QUIZ CHAPTER FIFTEEN

2. Opening Day, Today: 3:00 p.m.

3. 1. A statistical procedure used to describe the strength and direction of the linear relationship between two factors is called
effect size
power
hypothesis testing
coincidence
a correlation

4. 1. A statistical procedure used to describe the strength and direction of the linear relationship between two factors is called
effect size
power
hypothesis testing
coincidence
a correlation

5. The strength and direction of a correlation are measured by the correlation coefficient which is represented as: μ  σ r cc

6. 2. The strength and direction of a correlation are measured by the correlation coefficient which is represented as: μ  σ r cc

7. 3. A researcher measures the following correlation between cups of coffee consumed daily and daily work schedule. Which description best explains the relationship between these two factors?
The more a person works, the more coffee he or she tends to drink.
The less a person works, the more coffee he or she tends to drink.
The more a person works, the less coffee he or she tends to drink.
No linear pattern is evident.

8. 3. A researcher measures the following correlation between cups of coffee consumed daily and daily work schedule. Which description best explains the relationship between these two factors?
The more a person works, the more coffee he or she tends to drink.
The less a person works, the more coffee he or she tends to drink.
The more a person works, the less coffee he or she tends to drink.
No linear pattern is evident.

9. 4. With correlation data we cannot talk about:
a relationship between variables
prediction
one moving with another
one variable causing another
all of the above

10. 4. With correlation data we cannot talk about:
a relationship between variables
prediction
one moving with another
one variable causing another
all of the above

11. 5. R2 or ________ is the proportion of variance in one variable that can be explained by the second.
Times square
the coefficient of determination
the sum of squares
The Chi Square test
analysis of variance

12. 5. R2 or ________ is the proportion of variance in one variable that can be explained by the second.
Times square
the coefficient of determination
the sum of squares
The Chi Square test
analysis of variance

13. 6. Which of the following indicates the strongest correlation?

14. 6. Which of the following indicates the strongest correlation?

15. 7. The correlation coefficient ranges from –1. 0 to +1
7. The correlation coefficient ranges from –1.0 to +1.0, with values closer to ±1.0 indicating
a more positive relationship between two factors
a stronger relationship between two factors
that two factors are less likely to be related
that the correlation is due to outliers
all of the above

16. 7. The correlation coefficient ranges from –1. 0 to +1
7. The correlation coefficient ranges from –1.0 to +1.0, with values closer to ±1.0 indicating
a more positive relationship between two factors
a stronger relationship between two factors
that two factors are less likely to be related
that the correlation is due to outliers
all of the above

17. 8. The correlation coefficient measures the extent to which changes in one factor are _______ in a second factor.
related to changes
causing changes
causing variability
exactly mirrored
all of the above

18. 8. The correlation coefficient measures the extent to which changes in one factor are _______ in a second factor.
related to changes
causing changes
causing variability
exactly mirrored
all of the above

19. 9. The most common measure of effect size for the correlation coefficient is called
the coefficient of determination
estimated Cohen's d
the test statistic

20. 9. The most common measure of effect size for the correlation coefficient is called
the coefficient of determination
estimated Cohen's d
the test statistic

21. 10. The coefficient of determination is
a measure of effect size
mathematically equivalent to eta- squared
equal to the correlation coefficient squared
all of the above

22. 10. The coefficient of determination is
a measure of effect size
mathematically equivalent to eta- squared
equal to the correlation coefficient squared
all of the above

23. The End