Statistical Significance and Statistical Reporting: Moving Beyond Binary

doi:10.1177/00222429231216910

Statistical Significance and Statistical Reporting: Moving Beyond Binary

2024-02-07

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Blakeley B. McShane *

DOI：10.1177/00222429231216910

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Null hypothesis significance testing (NHST) is the default approach to statistical analysis and reporting in marketing and the biomedical and social sciences more broadly. Despite its default role, NHST has long been criticized by both statisticians and applied researchers, including those within marketing. Therefore, the authors propose a major transition in statistical analysis and reporting. Specifically, they propose moving beyond binary: abandoning NHST as the default approach to statistical analysis and reporting. To facilitate this, they briefly review some of the principal problems associated with NHST. They next discuss some principles that they believe should underlie statistical analysis and reporting. They then use these principles to motivate some guidelines for statistical analysis and reporting. They next provide some examples that illustrate statistical analysis and reporting that adheres to their principles and guidelines. They conclude with a brief discussion.

Keywords:

null hypothesis significance testing

P-value

replication

sociology of science

statistical significance

Statistical Significance and Statistical Reporting: Moving Beyond Binary

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