## EDUC 812 Quiz Correlation

**EDUC 812 Quiz Correlation**

Covers the Textbook material from Module 6: Week 6.

- 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: - 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? - The assumption of linearity is met if the relationship is curvilinear.
- What does the sign of (+ or -) best represent?
- When running a Pearson Correlation, if
*p*< .05, then reject the null, or in other words, there is a significant relationship. - 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? - When data screening for a Pearson Correlation, you should make Box and Whisker plots to identify bivariate outliers.
- 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? - If X and Y are completely unrelated,
*r*will be close to 1. - The
*r*-value shows if there is a difference between the two variables being tested. - A positive correlation between two variables, X and Y, indicates that:
- The Pearson Product Moment correlation is used to determine if there is a relationship between two variables.
- What type of graph best represents a correlation?
- 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. - Suppose that you want to run 4 correlations, and you want your Experiment Wise α (
*EW*α) to be .05. What Per-Comparison α (*PC*α) would you use if you applied the Bonferroni procedure? - What type of relationship does this scatterplot best represent?
- Visual examination of a _________ is a reasonable way to detect bivariate outliers for a Pearsons correlation.
- Which of the following correlations represents the strongest possible relationship between X and Y?:
- It is appropriate to make a causal inference based on Pearson’s
*r* - 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? - The sign (+/-) of
*r*provides information about the strength of the relationship between X and Y. - A negative correlation between two variables, X and Y, indicates that:
- Linearity is an assumption for the Pearson Correlation.
- A linear relation looks like a bell-shaped curve.
- Pearson’s
*r*(50) = .75,*p*= .03 can be interpreted as:

Set 2

- Visual examination of a _________ is a reasonable way to detect bivariate outliers for a Pearsons correlation.
- What does the sign of (+ or -) best represent?
- What type of relationship does this scatterplot best show?
- Suppose that you want to run 4 correlations, and you want your Experiment Wise α (
*EW*α) to be .05. What Per-Comparison α (*PC*α) would you use if you applied the Bonferroni procedure? - 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? - 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? - A correlation near 0 indicates:
- Which of the following correlations represents the strongest possible relationship between X and Y?:
- 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: - The
*r*-value shows if there is a difference between the two variables being tested. - A linear relation looks like a bell-shaped curve.
- The Pearson Product Moment correlation is used to determine if there is a relationship between two unrelated variables.
- When running a Pearson Correlation, if
*p*< .05, then reject the null, or in other words, there is a signicant relationship. - When data screening for a Pearson Correlation, you should make Box and Whisker plots to identify bivariate outliers.
- Pearson’s
*r*(50) = .75,*p*= .03 can be interpreted as: - 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? - The sign (+/-) of
*r*provides information about the strength of the relationship between X and Y. - It is appropriate to make a causal inference based on Pearson’s
*r* - The result for a Pearson’s
*r*between students’ anxiety and their achievement was,*r(*90) = – .75,*p*= .03. What can the researcher conclude? - The assumption of linearity is met if the relationship is curvilinear.
- If X and Y are completely unrelated,
*r*will be close to 1. - Linearity is an assumption for the Pearson Correlation.
- What type of graph best represents a correlation?
- What type of relationship does this scatterplot best represent?
- Bivariate normal distributions is an assumption for the Pearson Correlation.