Question

Kibler Chapter 18 Homework

1 .
A correlational study found that the correlation between spousal relationship quality and
cardiovascular risk was -0.72.
Fully interpret the correlation (using he first three statements as in Chapter 9):
Calculate the percent of variance in cardiovascular risk accounted for by spousal relationship
quality (this is the same as the degree of relationship). Show your work.

% variance _________________

Based on these results would you say that spousal relationship quality influences cardiovascular
risk? Why or why not?


2 . A t = 2.08 (p<.05) was computed in a study which had 13 participants per group (24 degrees
of freedom). The mean of the first group was 4.68 and the mean of the second group was 2.68.
The estimate of the population standard deviation was 1.00. Compute the effect size. Indicate
whether it is small, medium or large effect size, and report the full results of the t-test analysis.

Answer 1

51.84%.

t(24) = 2.08, p < .05, d = 2.00.

Step-by-step explanation:

The correlation coefficient between spousal relationship quality and cardiovascular risk is -0.72.

The negative sign indicates an inverse relationship between the two variables.

The absolute value of the correlation coefficient indicates a strong relationship between the two variables.

To calculate the percent of variance accounted for by spousal relationship quality:

Square the correlation coefficient to get the coefficient of determination: 0.72^2 = 0.5184.

Multiply by 100 to get the percent: 0.5184 x 100 = 51.84%.

Based on these results, it can be said that there is a strong negative relationship between spousal relationship quality and cardiovascular risk. However, correlation does not necessarily imply causation, so it cannot be definitively stated that spousal relationship quality influences cardiovascular risk.

To compute the effect size:

Calculate Cohen's d: d = (mean1 - mean2) / estimated standard deviation = (4.68 - 2.68) / 1.00 = 2.00.

Determine the magnitude of the effect size using Cohen's criteria: a d of 2.00 is considered a large effect size.

The full results of the t-test analysis are:

t(24) = 2.08, p < .05, d = 2.00.

This indicates that the difference between the two groups is statistically significant and has a large effect size.