A great article on how the Naymen-Pearson Hypothesis Testing is not particularly useful as a method of inference (e.g. the way most people tend to think of stat

A great article on how the Naymen-Pearson Hypothesis Testing is not particularly useful as a method of inference (e.g. the way most people tend to think of statistics with p-values and 5% significance doesn't say much). Some of what he is saying is a little shoddy, since Fisher actually came up with a much more robust, but less used, method of inference called Maximum likelihood estimation (MLE), which currently stands with The Bayesian Theory as the competing (yet partially complimentary) theories of statistical inference. Strict, but arbitrary, distinction between the null H0 and alternative H1 hypotheses, which is what p-values suggest, is as careless as the article points out.