The Art of Statistics: Learning from Data

by David Spiegelhalter

As we shall see in the next chapter, Neyman and Pearson had vehement, even publicly abusive, arguments with Fisher over the appropriate form of hypothesis testing, and this conflict has never been resolved into a single ‘correct’ approach. The Heart Protection Study shows that clinical trials tend to be designed from a Neyman–Pearson perspective but, strictly speaking, size and power are irrelevant once the experiment has actually been carried out. At this point the trial is analysed using confidence intervals to show the plausible values for the treatment effects, and Fisherian P-values to summarize the strength of the evidence against the null hypothesis. So an odd mixture of Fisher’s and Neyman–Pearson’s ideas has proven to be remarkably effective.

Alternative approaches