000			02203nam a22003017a 4500
003			OSt
005			20250226142402.0
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020			_a9781107054134
020			_a9781107664647
040			_aNISER LIBRARY _beng _cNISER LIBRARY
041			_aEnglish
082			_a519.23 _bMAY-S
100			_aMayo, Deborah G.
245			_aStatistical inference as severe testing : _bhow to get beyond the statistics wars
260			_aCambridge : _bCambridge University Press, _c2018.
300			_axvi, 486p. : _billustrations ; _c23 cm
504			_aIncludes bibliographical references and index
520			_aMounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
650			_aMathematical statistics
650			_aInference
650			_aError analysis (Mathematics)
650			_aFallacies (Logic)
650			_aDeviation (Mathematics)
856			_3Table of Contents _uhttps://assets.cambridge.org/97811070/54134/toc/9781107054134_toc.pdf
856			_3Reviews _uhttps://www.goodreads.com/book/show/37684125-statistical-inference-as-severe-testing#CommunityReviews
942			_2udc _cBK
999			_c35355 _d35355