The Art of Statistics: Learning from Data

by David Spiegelhalter

This term was popularized by Ronald Fisher in the 1920s and, in spite of the criticisms we shall see later, continues to play a major role in statistics. Ronald Fisher was an extraordinary, but difficult, man. He was extraordinary because he is regarded as a pioneering figure in two distinct fields – genetics and statistics. Yet he had a notorious temper and could be extremely critical of anyone who he felt questioned his ideas, while his support for eugenics and his public criticism of the evidence for the link between smoking and lung cancer damaged his standing. His personal reputation has suffered as his financial connections with the tobacco industry have been revealed, but his scientific reputation is undiminished, as his ideas find repeated new applications in the analysis of large data sets. As I mentioned in Chapter 4, Fisher developed the idea of randomization in agricultural trials while working at Rothamsted Experimental Station. He further illustrated the ideas of randomization in experimental design with his famous tea tasting test, in which a woman (thought to be a Muriel Bristol) claimed to be able to tell by tasting a cup of tea whether the milk had been added before or after tea was poured into a cup. Four cups with milk first, and four with tea first, were prepared and the eight cups were presented in a random order; Muriel was told there were four of each, and had to guess which four had milk first. She is said to have got them all right, which another ...

Ronald fischer and p value statistical significance in random trials