Essay

A researcher conducts a study on a new cognitive training app and finds a statistically significant relationship between app usage and working memory performance (p<.05p < .05). Applying the criticism regarding the limited informativeness of rejecting the null hypothesis, explain why this result alone is insufficient for evaluating the app's real-world utility and how the researcher should improve their reporting.

Question: A researcher conducts a study on a new cognitive training app and finds a statistically significant relationship between app usage and working memory performance (p<.05p < .05). Applying the criticism regarding the limited informativeness of rejecting the null hypothesis, explain why this result alone is insufficient for evaluating the app's real-world utility and how the researcher should improve their reporting.

Sample answer: Simply rejecting the null hypothesis (p<.05p < .05) only indicates that the relationship between app usage and working memory is nonzero. However, it does not describe the actual magnitude (effect size) of this relationship, which is crucial for determining its practical significance. Additionally, since real-world relationships are rarely exactly zero, rejecting the null hypothesis may merely confirm a trivial difference. To make this finding informative, the researcher must report a measure of effect size (e.g., Cohen's dd or Pearson's rr) to indicate the strength and practical importance of the effect.

Key points:

  • Rejecting the null hypothesis only indicates the relationship is nonzero.
  • The test fails to describe the actual magnitude or practical significance of the effect.
  • Population relationships are rarely exactly zero, making null rejection trivial on its own.
  • Researchers must report effect sizes (e.g., Cohen's dd or Pearson's rr) to resolve this limitation.

Rubric: A complete answer must: 1. Correctly apply the criticism that rejecting the null hypothesis only asserts a nonzero relationship. 2. Explain that the result does not describe the magnitude or effect size. 3. Note that population relationships are rarely exactly zero. 4. Propose reporting effect sizes (e.g., Cohen's dd or Pearson's rr) to provide the missing magnitude information.

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Updated 2026-05-27

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Research Methods in Psychology - 4th American Edition @ KPU

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