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Explain how these correlation results ( and ) 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 . Item 3 ('Self-Acceptance') and Item 25 ('Personal Growth') show a correlation of .
Question: Explain how these correlation results ( and ) 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 between Item 3 and Item 12 is expectedly strong because both belong to the 'Self-Acceptance' cluster. Conversely, the correlation of 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 ( and ) 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 () because they belong to the same cluster, and between-cluster variables (Item 3 and 25) have a weak correlation () because they are in different clusters, verifying the statistical division of clusters.
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Research Methods in Psychology - 4th American Edition @ KPU
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