Skip to content
Cart

Your Cart

×

You have 0 items in your cart.

Register Sign in Wishlist

Statistical Inference as Severe Testing
How to Get Beyond the Statistics Wars

$29.99 (P)

  • Date Published: September 2018
  • availability: Available
  • format: Paperback
  • isbn: 9781107664647

$ 29.99 (P)
Paperback

Add to cart Add to wishlist

Other available formats:
Hardback, eBook


Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • 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.

    • Views a contentious debate as a difference in goals to enable fair-minded engagement
    • Refocuses on the goal of learning from error to shed fresh light on statistical inference
    • Offers a bridge between long-standing philosophical problems and concerns of practicing scientists and statisticians
    Read more

    Reviews & endorsements

    'Deborah G. Mayo argues forcefully for a frequentist position on statistical inference, and it is a pleasure to see how passionately she treats the various issues analyzed. Her writing style is highly engaging and conversational: in her frequent recourses to the first person, one can almost hear the dialogue between herself and the various people with whom she debates. The book is at the same time of highest scientific quality. It may qualify as one of the liveliest books on the philosophy of statistical inference.' Gerd Gigerenzer, Max Planck Institute for Human Development

    'Written as a series of tours and excursions, Deborah G. Mayo's lively book revisits the foundations of statistical inference from a simple and clear premise: only trust results that pass `severe tests'. Her ideas can be thought of as a modern, more complete version of Popper's notion of falsifiability. She goes beyond the usual Bayesian versus frequentist controversy and deals with pressing practical issues such as the crisis in scientific reproducibility. Whether you agree or disagree with her ideas, you will find the journey entertaining and thought provoking.' Larry Wasserman, Carnegie Mellon University, Pennsylvania

    'An extraordinary and enlightening grand tour through centuries of philosophical discourse underpinning modern statistics. Mayo's important contribution to this discourse, the severity principle, offers clarifying insight to several of the statistical conundrums all too often confounding even the brightest of modern data analysts and statistical theorists. I look forward to severity calculations eventually appearing alongside confidence intervals in statistical computer programs and journal discussions of findings.' Steven McKinney, British Columbia Cancer Research Centre

    'Whether or not you agree with her basic stance on statistical inference, if you are interested in the subject, and all scientists ought to be, Deborah G. Mayo’s writings are a must. Her views on inference are all the more valuable for being contrary to much current consensus. Her latest book will delight many and infuriate others but force all who are serious about these issues to think. Her capacity to jolt the complacent is second to none.' Stephen Senn, author of Dicing with Death

    'Deborah G. Mayo’s insights into the philosophical dimensions of these problems are unsurpassed in their originality, their importance, and the breadth of understanding on which they are based. Here she combines perspectives from philosophy of science and the foundations of statistics to eliminate mirages produced by misunderstandings both philosophical and statistical, while putting into focus the ways in which her error-statistical approach is relevant to current problems of scientific inquiry in various disciplines.' Kent Staley, Saint Louis University, Missouri

    'In this new book that reviews several competing paradigms for the philosophy of statistics in science, Deborah G. Mayo continues her project of untangling and delineating methods, models, assumptions, and goals, with an aim of moving toward pragmatic modes of inference that go beyond wishful thinking.' Andrew Gelman, Columbia University, New York

    'In this ground-breaking volume, Deborah G. Mayo cuts through the thicket of confusion surrounding debates on statistical inference, debunking the many widespread misconceptions about statistical tests and developing the theory of error statistics and severe testing. The book should be read by all practicing statisticians, and indeed by all scientists and others trying to extract meaning from data.' David J. Hand, Imperial College, London

    'This book is a detailed elaboration of the idea that statistical inferences are well-founded only if the possible ways in which they could be erroneous have been identified and responded to. The ramifications of this standpoint lead Mayo to solutions of long-standing problems in the philosophy of statistics, shows the way towards reforms in common but dubious statistical practices and helps the non-expert make informed judgements about such matters. This book is destined to become a definitive and frequently consulted resource.' Alan Chalmers, University of Sydney

    'The book by Deborah G. Mayo is a timely examination of the use of statistics in science. Her severity requirement demands that the scientist provide a sharp question and related data. Absent that, the observer should withhold judgement or outright reject. It is time to get tough. Funding agencies should take note.' S. Stanley Young, FASA, FAAAS

    See more reviews

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity

    ×

    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?

    ×

    Product details

    • Date Published: September 2018
    • format: Paperback
    • isbn: 9781107664647
    • length: 500 pages
    • dimensions: 228 x 151 x 23 mm
    • weight: 0.81kg
    • availability: Available
  • Table of Contents

    Preface
    Excursion 1. How to Tell What's True about Statistical Inference: Tour I. Beyond probabilism and performance
    Tour II. Error probing tools vs. logics of evidence
    Excursion 2. Taboos of Induction and Falsification: Tour I. Induction and confirmation
    Tour II. Falsification, pseudoscience, induction
    Excursion 3. Statistical Tests and Scientific Inference: Tour I. Ingenious and severe tests
    Tour II. It's the methods, stupid
    Tour III. Capability and severity: deeper concepts
    Excursion 4. Objectivity and Auditing: Tour I. The myth of 'the myth of objectivity'
    Tour II. Rejection fallacies: whose exaggerating what?
    Tour III. Auditing: biasing selection effects and randomization
    Tour IV. More auditing: objectivity and model checking
    Excursion 5. Power and Severity: Tour I. Power: pre-data and post-data
    Tour II. How not to corrupt power
    Tour III. Deconstructing the N-P vs. Fisher debates
    Excursion 6. (Probabilist) Foundations Lost, (Probative) Foundations Found: Tour I. What ever happened to Bayesian foundations?
    Tour II. Pragmatic and error statistical Bayesians
    Souvenir (Z) farewell
    References
    Index.

  • Author

    Deborah G. Mayo, Virginia Tech
    Deborah G. Mayo is Professor Emerita in the Department of Philosophy at Virginia Tech. Author of Error and the Growth of Experimental Knowledge (1996), she won the 1998 Lakatos Prize for an outstanding contribution to philosophy of science. She directed the NEH Summer Seminar (1999) on Philosophy of Experimental Inference. She co-founded, with G. W. Chatfield, the Fund for Experimental Reasoning, Reliability and Objectivity and Rationality (E.R.R.O.R) in 2006 which has co-sponsored 10 conferences, workshops and distinguished lecture series. She's a visiting professor at the London School of Economics and Political Science, Centre for the Philosophy of Natural and Social Science (CPNSS) (2007–present).

Sign In

Please sign in to access your account

Cancel

Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email lecturers@cambridge.org

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×

Find content that relates to you

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.

Cancel

Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

×
Please fill in the required fields in your feedback submission.
×