Case Study

Based on the computational formula for Pearson's rr, diagnose the student's mathematical error and explain what the student actually calculated compared to what the formula requires.

Case context: A psychology undergraduate student is trying to calculate the correlation between self-reported anxiety and test performance for their lab group. They have successfully converted all raw scores into zz scores and multiplied the anxiety and test performance zz scores together for each participant, creating a column of cross-products. The student then sums this entire column and reports the total sum ((zxzy)\sum(z_xz_y)) as the Pearson's rr correlation coefficient.

Question: Based on the computational formula for Pearson's rr, diagnose the student's mathematical error and explain what the student actually calculated compared to what the formula requires.

Sample answer: The student's error is that they stopped after summing the cross-products. According to the computational formula, r=(zxzy)Nr = \frac{\sum(z_xz_y)}{N}, Pearson's rr represents the mean of the cross-products, not just the sum. By stopping early, the student calculated the total sum of cross-products. To find the correct correlation coefficient, the student must divide their total sum by NN, which represents the sample size.

Key points:

  • Diagnoses that the student stopped prematurely at the summation step.
  • Explains that Pearson's rr is the mean cross-product, not the sum of cross-products.
  • States that the student needs to divide the sum of the cross-products by NN to find the correct coefficient.

Rubric: A correct response must identify that the student found the sum rather than the mean, and explain that dividing the sum by NN is required to complete the formula.

0

1

Updated 2026-05-27

Contributors are:

Who are from:

Tags

KPU

Research Methods in Psychology - 4th American Edition @ KPU

Related