05, is statistically unsound. For exploratory research generating hypotheses, a wider range of evidence is often more valuable than a single, potentially unstable p value.
When Not To Trust P Value Results: Navigating Statistical Traps
A robust conclusion is built upon a convergence of evidence from multiple studies, using different methods, populations, and theoretical frameworks. A p value is a probability calculated under a specific statistical model, and it does not measure the probability that the studied hypothesis is true, nor does it quantify the magnitude or importance of an effect.
05 is a convention, not a natural boundary in the data. Conversely, confirmatory studies in fields like medicine may still rely on strict thresholds for regulatory approval, but even there, the evidence is increasingly expected to be multifaceted.
When Not To Trust P Value Results
By considering the probability of a hypothesis given the observed data, Bayesian analysis offers a more intuitive and often more informative alternative, particularly for complex models and when prior research exists. The Cultural Shift Away from P-Value Worship.
More About When to reject p value
Looking at When to reject p value from another angle can help expand the discussion and give readers a second clear paragraph under the same section.
More perspective on When to reject p value can make the topic easier to follow by connecting earlier points with a few simple takeaways.
