Confusion surrounding the reporting and interpretation of results of classical statistical tests is widespread among applied researchers. ... The distinction between evidence (p’s) and errors (α’s) is no semantic quibble. Instead it illustrates the fundamental differences between Fisher’s ideas on significance testing and inductive inference, and Neyman–Pearson views on hypothesis testing and inductive behavior. ... A consequence of this is the number of “statistically significant effects” later found to be negligible, to the embarrassment of the statistical community.
