## EDUC 812 Quiz Correlation

EDUC 812 Quiz Correlation

Covers the Textbook material from Module 6: Week 6.

1. In a study examining the relationship between coffee consumption and heart disease, the researcher obtained a value of r(120) = -.88, p = .04. The results conclude:
2. The result for a Pearson’s r for online, university students’ perceived learning and their sense of community was, r(22) = .13, p = .27. What can the researcher conclude?
3. The assumption of linearity is met if the relationship is curvilinear.
4. What does the sign of (+ or -) best represent?
5. When running a Pearson Correlation, if p < .05, then reject the null, or in other words, there is a significant relationship.
6. The result for a Pearson’s r between students’ test scores and their motivation was, r(24) = .32, p = .07. What can the researcher conclude?
7. When data screening for a Pearson Correlation, you should make Box and Whisker plots to identify bivariate outliers.
8. The result for a Pearson’s r for students’ perceived learning and their sense of community was, r(45) = .72, p = .02. What can the researcher conclude?
9. If X and Y are completely unrelated, r will be close to 1.
10. The r-value shows if there is a difference between the two variables being tested.
11. A positive correlation between two variables, X and Y, indicates that:
12. The Pearson Product Moment correlation is used to determine if there is a relationship between two variables.
13. What type of graph best represents a correlation?
14. The researcher rejected the null hypothesis at the 95% confidence level where r(14) = .72, p = .002. The effect size was very small and the relationship was negative.
15. Suppose that you want to run 4 correlations, and you want your Experiment Wise α (EWα) to be .05. What Per-Comparison α (PCα) would you use if you applied the Bonferroni procedure?
16. What type of relationship does this scatterplot best represent?
17. Visual examination of a _________ is a reasonable way to detect bivariate outliers for a Pearsons correlation.
18. Which of the following correlations represents the strongest possible relationship between X and Y?:
19. It is appropriate to make a causal inference based on Pearson’s r
20. After running a Pearson correlation, the researcher obtained the following results r(98) = .32, p = .02. Based on this information, what was the sample size?
21. The sign (+/-) of r provides information about the strength of the relationship between X and Y.
22. A negative correlation between two variables, X and Y, indicates that:
23. Linearity is an assumption for the Pearson Correlation.
24. A linear relation looks like a bell-shaped curve.
25. Pearson’s r(50) = .75, p = .03 can be interpreted as:

Set 2

1. Visual examination of a _________ is a reasonable way to detect bivariate outliers for a Pearsons correlation.
2. What does the sign of (+ or -) best represent?
3. What type of relationship does this scatterplot best show?
4. Suppose that you want to run 4 correlations, and you want your Experiment Wise α (EWα) to be .05. What Per-Comparison α (PCα) would you use if you applied the Bonferroni procedure?
5. The result for a Pearson’s r for students’ perceived learning and their sense of community was, r(45) = .72, p = .02. What can the researcher conclude?
6. After running a Pearson correlation, the researcher obtained the following results r(98) = .32, p = .02. Based on this
information, what was the sample size?
7. A correlation near 0 indicates:
8. Which of the following correlations represents the strongest possible relationship between X and Y?:
9. In a study examining the relationship between coffee consumption and heart disease, the researcher obtained a value of r(120) = -.88, p = .04. The results conclude:
10. The r-value shows if there is a difference between the two variables being tested.
11. A linear relation looks like a bell-shaped curve.
12. The Pearson Product Moment correlation is used to determine if there is a relationship between two unrelated variables.
13. When running a Pearson Correlation, if p < .05, then reject the null, or in other words, there is a signicant relationship.
14. When data screening for a Pearson Correlation, you should make Box and Whisker plots to identify bivariate outliers.
15. Pearson’s r(50) = .75, p = .03 can be interpreted as:
16. The result for a Pearson’s r between students’ test scores and their motivation was, r(24) = .32, p = .07. What can the researcher conclude?
17. The sign (+/-) of r provides information about the strength of the relationship between X and Y.
18. It is appropriate to make a causal inference based on Pearson’s r
19. The result for a Pearson’s r between students’ anxiety and their achievement was, r(90) = – .75, p = .03. What can the researcher conclude?
20. The assumption of linearity is met if the relationship is curvilinear.
21. If X and Y are completely unrelated, r will be close to 1.
22. Linearity is an assumption for the Pearson Correlation.
23. What type of graph best represents a correlation?
24. What type of relationship does this scatterplot best represent?
25. Bivariate normal distributions is an assumption for the Pearson Correlation.
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