Statistical Inference As Severe Testing PDF Download
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| Author | : Deborah G. Mayo |
| Publisher | : Cambridge University Press |
| Total Pages | : 503 |
| Release | : 2018-09-20 |
| Genre | : Mathematics |
| ISBN | : 1108563309 |
Download Statistical Inference as Severe Testing Book in PDF, ePub and Kindle
Mounting 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.
| Author | : Deborah G. Mayo |
| Publisher | : University of Chicago Press |
| Total Pages | : 520 |
| Release | : 1996-07-15 |
| Genre | : Mathematics |
| ISBN | : 9780226511979 |
Download Error and the Growth of Experimental Knowledge Book in PDF, ePub and Kindle
Preface1: Learning from Error 2: Ducks, Rabbits, and Normal Science: Recasting the Kuhn's-Eye View of Popper 3: The New Experimentalism and the Bayesian Way 4: Duhem, Kuhn, and Bayes 5: Models of Experimental Inquiry 6: Severe Tests and Methodological Underdetermination7: The Experimental Basis from Which to Test Hypotheses: Brownian Motion8: Severe Tests and Novel Evidence 9: Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance10: Why You Cannot Be Just a Little Bit Bayesian 11: Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics12: Error Statistics and Peircean Error Correction 13: Toward an Error-Statistical Philosophy of Science ReferencesIndex Copyright © Libri GmbH. All rights reserved.
| Author | : Therese M. Donovan |
| Publisher | : Oxford University Press, USA |
| Total Pages | : 430 |
| Release | : 2019 |
| Genre | : Mathematics |
| ISBN | : 0198841299 |
Download Bayesian Statistics for Beginners Book in PDF, ePub and Kindle
This is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.
| Author | : Deborah G. Mayo |
| Publisher | : Cambridge University Press |
| Total Pages | : 491 |
| Release | : 2009-10-26 |
| Genre | : Science |
| ISBN | : 1139485369 |
Download Error and Inference Book in PDF, ePub and Kindle
Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing.
| Author | : Deborah G. Mayo |
| Publisher | : Cambridge University Press |
| Total Pages | : 503 |
| Release | : 2018-09-20 |
| Genre | : Mathematics |
| ISBN | : 1107054133 |
Download Statistical Inference as Severe Testing Book in PDF, ePub and Kindle
Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.
| Author | : Aris Spanos |
| Publisher | : Cambridge University Press |
| Total Pages | : 787 |
| Release | : 2019-09-19 |
| Genre | : Business & Economics |
| ISBN | : 1107185149 |
Download Probability Theory and Statistical Inference Book in PDF, ePub and Kindle
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
| Author | : Will Kurt |
| Publisher | : No Starch Press |
| Total Pages | : 258 |
| Release | : 2019-07-09 |
| Genre | : Mathematics |
| ISBN | : 1593279566 |
Download Bayesian Statistics the Fun Way Book in PDF, ePub and Kindle
Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples. By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to: - How to measure your own level of uncertainty in a conclusion or belief - Calculate Bayes theorem and understand what it's useful for - Find the posterior, likelihood, and prior to check the accuracy of your conclusions - Calculate distributions to see the range of your data - Compare hypotheses and draw reliable conclusions from them Next time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.
| Author | : D. R. Cox |
| Publisher | : Cambridge University Press |
| Total Pages | : 227 |
| Release | : 2006-08-10 |
| Genre | : Mathematics |
| ISBN | : 1139459139 |
Download Principles of Statistical Inference Book in PDF, ePub and Kindle
In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.
| Author | : Ali Almossawi |
| Publisher | : The Experiment, LLC |
| Total Pages | : 66 |
| Release | : 2014-09-23 |
| Genre | : Philosophy |
| ISBN | : 1615192263 |
Download An Illustrated Book of Bad Arguments: Learn the Lost Art of Making Sense (Bad Arguments) Book in PDF, ePub and Kindle
“This short book makes you smarter than 99% of the population. . . . The concepts within it will increase your company’s ‘organizational intelligence.’. . . It’s more than just a must-read, it’s a ‘have-to-read-or-you’re-fired’ book.”—Geoffrey James, INC.com From the author of An Illustrated Book of Loaded Language, here’s the antidote to fuzzy thinking, with furry animals! Have you read (or stumbled into) one too many irrational online debates? Ali Almossawi certainly had, so he wrote An Illustrated Book of Bad Arguments! This handy guide is here to bring the internet age a much-needed dose of old-school logic (really old-school, a la Aristotle). Here are cogent explanations of the straw man fallacy, the slippery slope argument, the ad hominem attack, and other common attempts at reasoning that actually fall short—plus a beautifully drawn menagerie of animals who (adorably) commit every logical faux pas. Rabbit thinks a strange light in the sky must be a UFO because no one can prove otherwise (the appeal to ignorance). And Lion doesn’t believe that gas emissions harm the planet because, if that were true, he wouldn’t like the result (the argument from consequences). Once you learn to recognize these abuses of reason, they start to crop up everywhere from congressional debate to YouTube comments—which makes this geek-chic book a must for anyone in the habit of holding opinions.
| Author | : Larry Wasserman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 446 |
| Release | : 2013-12-11 |
| Genre | : Mathematics |
| ISBN | : 0387217363 |
Download All of Statistics Book in PDF, ePub and Kindle
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
