Analytic Resources

Issues with NHST

Research By Design: What Statistical Significance Really Means (18:13)

The Journal of Experimental Education- Problems With Null Hypothesis Significance Testing (NHST): What Do the Textbooks Say?

Advanced Statistics (Using R)- Criticisms of Null Hypothesis Testing and p-value

There have been criticisms since the use of the null hypothesis testing (NHT) and this chapter summarizes the main criticisms.

When Null Hypothesis Significance Testing Is Unsuitable for Research: A ReassessmentNull hypothesis significance testing (NHST) has several shortcomings that are likely contributing factors behind the widely debated replication crisis of (cognitive) neuroscience, psychology, and biomedical science in general. We review these shortcomings and suggest that, after sustained negative experience, NHST should no longer be the default, dominant statistical practice of all biomedical and psychological research. If theoretical predictions are weak we should not rely on all or nothing hypothesis tests. Different inferential methods may be most suitable for different types of research questions. Whenever researchers use NHST they should justify its use, and publish pre-study power calculations and effect sizes, including negative findings. Hypothesis-testing studies should be pre-registered and optimally raw data published. The current statistics lite educational approach for students that has sustained the widespread, spurious use of NHST should be phased out.

CrashCourse: P-Value Problems (12:13)

CrashCourse: P-Hacking (11:01)

CrashCourse: The Replication Crisis (14:35)

StatQuest: p-hacking: What it is and how to avoid it! (13:44)

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