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date: 28 January 2020

Abstract and Keywords

Bayesianism and frequentism are the two grand schools of statistical inference, divided by fundamentally different philosophical assumptions and mathematical methods. Bayesian inference models the subjective credibility of a hypothesis given a body of evidence, whereas frequentists focus on the reliability of inferential procedures. This chapter gives an overview of the principles, varieties and criticisms of Bayesianism and frequentism, compares both schools, taking in an examination of Deborah Mayo’s account of frequentism, an innovative proposal in which she presented as crucial the concept of degrees of severity; and applies them to salient topics in scientific inference, such as p-values, confidence intervals and optional stopping. author OK

Keywords: probability, statistical inference, Bayesianism, frequentism, p-value

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