Book Review: Fisher, Neyman, and the Creation of Classical Statistics

Erich Lehmann’s last book, which was published after his death, is on the history of classical statistics and its creators. Specifically, how his mentor Jerzy Neyman and his adversary Ronald Fisher helped lay the foundations for the methods that are used today in several fields. This post is intended to be a general review/summary of the book, which I recommend to everyone and anyone who is interested in statistics and science. Read More
fisher  math  power 

P-Values Are Tough And S-Values Can Help

The P-value doesn’t have many fans. There are those who don’t understand it, often treating it as a measure it’s not, whether that’s a posterior probability, the probability of getting results due to chance alone, or some other bizarre/incorrect interpretation. [1–3] Then there are those who dislike it for reasons such as believing that the concept is too difficult to understand or because they see it as a noisy statistic that provides something we’re not interested in. Read More

Misuse of Standard Error in Clinical Trials

Reporting effect sizes with their accompanying standard errors are necessary because it lets the reader interpret the magnitude of the treatment effect and the amount of uncertainty in that estimate. It is magnitudes better than not providing any effect sizes at all and only focusing on statements of statistical significance. Although many authors provide standard errors with the intention of relaying the amount of uncertainty in the model, there are several misconceptions about when the standard error should be reported, and it is often misused. Read More