Institute for Mathematical Behavioral Sciences

In many scientific disciplines, the practice of p-value null-hypothesis testing is as widespread as ever. Despite its popularity, or perhaps because of it, most researchers are not aware of the statistical peculiarities of the p-value procedure. For instance, p-values are based on data that were never observed, and these hypothetical data are themselves influenced by subjective intentions. In addition, p-values do not quantify statistical evidence. This presentation illustrates these problems with p-value null-hypothesis testing with several concrete examples. A principled and practical alternative to inference via the p-value will be discussed.