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Case Study

Based on the scatterplot's shape and the calculated statistic, diagnose why Pearson's rr yielded a result close to zero and interpret what kind of statistical association is actually present.

Case context: A researcher studies the relationship between the amount of sleep people get per night and their level of depression. The data points form an upside-down "U" shape on a scatterplot, indicating that people getting around eight hours of sleep tend to be the least depressed, while those getting too little or too much sleep are more depressed. However, when the researcher calculates Pearson's rr, the result is close to zero.

Question: Based on the scatterplot's shape and the calculated statistic, diagnose why Pearson's rr yielded a result close to zero and interpret what kind of statistical association is actually present.

Sample answer: The researcher found a result close to zero because Pearson's rr only measures linear trends. The relationship present is actually a strong nonlinear relationship, where the association between sleep and depression changes direction and is best represented by a curved line rather than a single straight line.

Key points:

  • The relationship is nonlinear
  • The data points are best fit by a curved line
  • Pearson's rr only measures linear relationships

Rubric: 1 point for identifying the relationship as a nonlinear relationship. 1 point for noting that the points are better fit by a curve. 1 point for diagnosing that Pearson's rr is near zero because it only captures straight-line (linear) patterns.

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Updated 2026-05-27

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Research Methods in Psychology - 4th American Edition @ KPU

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