Question 1

A correlation coefficient is also known as a:&#10;A) Spearman's rho.&#10;B) Pearson's r.&#10;C) Both A and B.&#10;D) None of the above.

Accepted Answer

A correlation coefficient can be referred to as both Spearman's rho and Pearson's r, as they are two common types of correlation coefficients used in statistics.

Question 2

Use the Pearson's r when:&#10;A) The distribution is asymmetrical.&#10;B) The data are at the ordinal level.&#10;C) The data are not curvilinear.&#10;D) The data are curvilinear.

Accepted Answer

Pearson's r is appropriate for linear relationships between two continuous variables. If the relationship is not linear (i.e., curvilinear), then Pearson's r is not appropriate. In addition, Pearson's r assumes a normal distribution, so it is not appropriate for highly skewed or asymmetrical data. When the data are at the ordinal level, Spearman's rho should be used instead. Therefore, the best choice is C.

Question 3

Use the Spearman's rho when:&#10;A) The distribution is symmetrical.&#10;B) The data are at the ordinal level.&#10;C) The data are curvilinear.&#10;D) The data are at the scale level.

Accepted Answer

Spearman's rho is used when the data are at the ordinal level, where the values are ranked and have no numerical meaning. It is a non-parametric test that measures the strength and direction of the relationship between two variables. It is not used when the distribution is symmetrical, when the data are at the scale level, or when the relationship between the variables is curvilinear.

Question 4

Use the following SPSS Statistics tool to calculate the correlation coefficient:&#10;A) Chart Builder&#8230;&#10;B) Descriptive Statistics&#8230;&#10;C) Bivariate&#8230;&#10;D) None of the above.

Accepted Answer

The Bivariate option allows us to calculate the correlation coefficient between two variables. Therefore, it is the best choice for this task.

Question 5

When variables share a curvilinear relationship, this relationship is also known as:&#10;A) Up and down&#10;B) Positive&#10;C) No relationship&#10;D) Non-linear

Accepted Answer

A curvilinear relationship means that the relationship between the variables is not a straight line or linear. Therefore, the correct answer is non-linear (option D). Options A, B, and C do not accurately describe a curvilinear relationship.

Question 6

Pearson's r is formally known as Pearson product-moment correlation coefficient.

Accepted Answer

Pearson's r is formally known as Pearson product-moment correlation coefficient.

Question 7

Spearman's rho is formally known as Spearman's rank-order correlation coefficient.

Accepted Answer

Spearman's rho is a commonly used statistical measure for the strength of the association between two ranked variables. It is also sometimes referred to as the Spearman's rank correlation coefficient.

Question 8

Use Pearson's r for data at the ordinal level.

Accepted Answer

Pearson's r is designed for data at the interval or ratio level, not ordinal. For ordinal data, Spearman's rank correlation coefficient is more appropriate.

Question 9

Use Spearman's rho for data at the scale level.

Accepted Answer

Spearman's rho is used for ordinal data or to measure rank correlations, not for data at the scale (interval or ratio) level.

Question 10

Use Pearson's r for data at the scale level.

Accepted Answer

Pearson's r is a measure of correlation between two variables at the scale level and is appropriate for data measured on an interval or ratio scale.

Deck 10: Correlation Coefficients: The Pearson R and Spearmans RHO