Reinhart points out that if a researcher runs an experiment and collects a huge sample of data then there is a high chance that they will find a statistically significant value for p when they do the analysis. This implies that:

Question

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The question discusses Reinhart’s point about large-sample studies yielding statistically significant p-values even when the practical significance may be questionable, which leads to the need for judgement in interpretation.
Option 1: 'It is not possible to interpret experiments with huge samples' This overstates the issue; interpretation is still possible, but requires careful judgement about what the p-value implies in context, effect sizes, and study design.
Option 2: 'It is better to run experiments with small samples' This is not a supported general guideline. Small samples can lead to imprecise estimates and low power, while large samples can inflate even trivial effects; the optimal sample size depends on the research question, power analysis, and practical constraints, not a blanket preference for small samples.
Option 3: 'p values are not useful' This is incorrect. P-values are useful for hypothesis testing, but they must be interpreted in context, considering effect size, confidence intervals, and study design; they are not the sole arbiter of truth.
Option 4: 'Interpreting the results of statistical tests requires judgement' This captures the nuance highlighted by Reinhart: large samples increase the chance of finding statistically significant p-values, so researchers must use judgment to assess practical significance, effect sizes, confidence intervals, and the broader context.
Option 5: 'Only experiments with huge samples can be interpreted' This is false; interpretation is possible across sample sizes, though the evidentiary strength and precision vary with sample size.

ATHK1X01 Mastery Quiz 05

Reinhart points out that if a researcher runs an experiment and collects a huge sample of data then there is a high chance that they will find a statistically significant value for p when they do the analysis. This implies that:

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