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Imagine you are developing a standardized research protocol for an upcoming psychology experiment. Based on the concept of p-hacking, describe three specific, actionable rules you would implement in your data analysis plan to prevent researchers in your lab from arbitrarily manipulating their data to artificially inflate their chances of obtaining a statistically significant result.

Question: Imagine you are developing a standardized research protocol for an upcoming psychology experiment. Based on the concept of p-hacking, describe three specific, actionable rules you would implement in your data analysis plan to prevent researchers in your lab from arbitrarily manipulating their data to artificially inflate their chances of obtaining a statistically significant result.

Sample answer: To prevent p-hacking in our lab, I would implement the following three rules. First, researchers must pre-register all dependent variables before data collection begins to prevent selectively reporting only the variables that yield a desirable pp-value. Second, the criteria for removing outliers must be explicitly defined and justified prior to analysis, ensuring no arbitrary removal of data points just to achieve significance. Third, researchers must report all findings, regardless of whether they are statistically significant or not, to prevent selectively presenting only the significant results.

Key points:

  • Establish strict, predefined criteria for outlier removal to prevent arbitrary data exclusion.
  • Commit to analyzing and reporting all dependent variables measured in the study.
  • Present all findings, including non-significant results, rather than selectively reporting only significant ones.

Rubric: Full credit requires identifying three distinct rules that directly address the mechanisms of p-hacking mentioned in the text (e.g., selective reporting of variables, arbitrary outlier removal, selective presentation of findings). Partial credit is awarded if fewer rules are provided or if the rules do not directly address the prevention of data manipulation meant to achieve a desirable pp-value.

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Updated 2026-05-27

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Research Methods in Psychology - 4th American Edition @ KPU

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