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Case Study

Explain how these correlation results (r=0.72r = 0.72 and r=0.08r = 0.08) align with the underlying statistical logic of factor analysis clusters.

Case context: A research team administers a 40-item questionnaire measuring psychological well-being. They apply factor analysis to organize the variables. The analysis outputs three clusters: 'Self-Acceptance', 'Positive Relations', and 'Personal Growth'. In the correlation table, Item 3 and Item 12 (both grouped under 'Self-Acceptance') show a correlation of r=0.72r = 0.72. Item 3 ('Self-Acceptance') and Item 25 ('Personal Growth') show a correlation of r=0.08r = 0.08.

Question: Explain how these correlation results (r=0.72r = 0.72 and r=0.08r = 0.08) align with the underlying statistical logic of factor analysis clusters.

Sample answer: Factor analysis works by grouping variables so that those within the same cluster are strongly correlated, while those in different clusters are weakly correlated. The correlation of r=0.72r = 0.72 between Item 3 and Item 12 is expectedly strong because both belong to the 'Self-Acceptance' cluster. Conversely, the correlation of r=0.08r = 0.08 between Item 3 and Item 25 is expectedly weak because they belong to different clusters ('Self-Acceptance' and 'Personal Growth'), showing they represent distinct aspects of well-being.

Key points:

  • Explain that variables within the same cluster (e.g., Item 3 and Item 12) must be strongly correlated.
  • Explain that variables across different clusters (e.g., Item 3 and Item 25) must show weak correlations.
  • Demonstrate understanding that the correlation values (r=0.72r = 0.72 and r=0.08r = 0.08) confirm the successful organization of these distinct clusters.

Rubric: The answer should correctly explain that within-cluster variables (Item 3 and 12) have a strong correlation (r=0.72r = 0.72) because they belong to the same cluster, and between-cluster variables (Item 3 and 25) have a weak correlation (r=0.08r = 0.08) because they are in different clusters, verifying the statistical division of clusters.

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Updated 2026-05-27

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Research Methods in Psychology - 4th American Edition @ KPU

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