This post is about the situation when developing statistical models, in which parameters are given with their means and standard errors, of ensuring that a data analyst does not mistakenly reject the null hypothesis for those parameters with small enough standard errors if those smaller standard errors were still ultimately the result of chance. Common correction methods for such assurance include but are not limited to the Bonferroni correction. This post discusses those correction methods as well as an alternative that I recently thought of. Follow the jump to see everything else, because even the introduction, which is meant to be a brief introduction to statistical models, is long enough that the jump would otherwise be too far below & would break the flow of this post for a reader.
