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Activity Number: 8 - Statistics and the Reproducibility Crisis
Type: Invited
Date/Time: Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
Sponsor: The American Statistician
Abstract #322369
Title: Resolving the Reproducibility Crisis Using Bayesian Inference
Author(s): Andrew Gelman* and Blake McShane
Companies: Columbia Unversity and Northwestern University
Keywords: Bayes ; reproducibility ; significance testing
Abstract:

Top science journals routinely publish ridiculous, scientifically implausible claims, justified based on "p < 0.05." And this in turn calls into question all sorts of more plausible, but not necessarily true, claims, that are supported by this same sort of evidence. To put it another way: we can all laugh at studies of ESP, or ovulation and voting, but what about MRI studies of political attitudes, or embodied cognition, or stereotype threat, or, for that matter, the latest potential cancer cure? If we can't trust p-values, does experimental science involving human variation just have to start over? And what to we do in fields such as political science and economics, where preregistered replication can be difficult or impossible? Can Bayesian inference supply a solution? Maybe. These are not easy problems, but they're important problems.


Authors who are presenting talks have a * after their name.

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