There is a logical flaw in the Statistical methods used across experimental science.
Ranging across math, philosophy, and culture, Bernoulli\'s Fallacy explains why something has gone wrong with how we use data--and how to fix it..
He contends that we need to take a Bayesian approach--that is, to incorporate prior knowledge when reasoning with incomplete information--in order to resolve the crisis.
Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for readers interested in the Statistical methods that frame our understanding of the world.
He highlights how influential nineteenth- and twentieth-century figures developed a Statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics.
Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.
Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics.
The foundation of the problem is a misunderstanding of probability and its role in making inferences from observations.
In an increasingly statistics-reliant society, this same deeply rooted error shapes decisions in medicine, law, and public policy with profound consequences.
This fault is not a minor academic quibble: it underlies a reproducibility Crisis now threatening entire disciplines.
There is a logical flaw in the Statistical methods used across experimental science
