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Willful Ignorance: The Mismeasure of Uncertainty Paperback – 1 Aug 2014


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Product details

  • Paperback: 452 pages
  • Publisher: Wiley-Blackwell; 1 edition (1 Aug. 2014)
  • Language: English
  • ISBN-10: 0470890444
  • ISBN-13: 978-0470890448
  • Product Dimensions: 15.6 x 2.3 x 23.4 cm
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Bestsellers Rank: 391,359 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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From the Back Cover

An original account of willful ignorance and how this principle relates to modern probability and statistical methods

Through a series of colorful stories about great thinkers and the problems they chose to solve, the author traces the historical evolution of probability and explains how statistical methods have helped to propel scientific research. However, the past success of statistics has depended on vast, deliberate simplifications amounting to willful ignorance, and this very success now threatens future advances in medicine, the social sciences, and other fields. Limitations of existing methods result in frequent reversals of scientific findings and recommendations, to the consternation of both scientists and the lay public.

Willful Ignorance: The Mismeasure of Uncertainty exposes the fallacy of regarding probability as the full measure of our uncertainty. The book explains how statistical methodology, though enormously productive and influential over the past century, is approaching a crisis. The deep and troubling divide between qualitative and quantitative modes of research, and between research and practice, are reflections of this underlying problem. The author outlines a path toward the re–engineering of data analysis to help close these gaps and accelerate scientific discovery. 

Willful Ignorance: The Mismeasure of Uncertainty presents essential information and novel ideas that should be of interest to anyone concerned about the future of scientific research. The book is especially pertinent for professionals in statistics and related fields, including practicing and research clinicians, biomedical and social science researchers, business leaders, and policy–makers.

About the Author

Herbert I. Weisberg, PhD, is Founder of Causalytics, LLC, which develops innovative technology for predictive analytics for both medical research and business applications. He was previously President of Correlation Research Inc., a consulting firm specializing in the application of statistics to various business and legal issues. A Fellow of the American Statistical Association, Dr. Weisberg has published numerous articles and two previous books related to applied statistics.


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By Su TOP 100 REVIEWER on 21 April 2015
Format: Paperback Vine Customer Review of Free Product ( What's this? )
Contrary to many people’s opinion the vast majority of my job is historical analysis – due to this we have a number of statistical programs and files which we are trialling to see if we can use them to help understand the reasons that people do what they do – like geographical mapping only more in the lines of similarities between cases and perpetrators.

Since analysis takes up so much of my subject accuracy in analysis is important to me, but those of us who deal with statistics on such a regular basis know how easy it is to manipulate those figures to suit particular requirements or goals.

Those of us who want honesty in our information remember the Disraeli quote “There are three kinds of lies: lies, damned lies and statistics” and we know that this is true.

Much of the problem lies with the way the statistics are raised and the way they are read – this book casts its net over the subject and raises many good points as well as a number of further questions which require more consideration.

This is a good book for those of us with an interest in the field but I would not suggest it as reading for anyone just passing. There are easier and clearer texts available but it is an interesting insight into one man's outlook.
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Format: Paperback Vine Customer Review of Free Product ( What's this? )
This book provides an original account of willful ignorance and how this principle relates to modern probability and statistical methods.

Its intended readership includes professionals in statistics and related fields, including practicing and research clinicians, biomedical and social science researchers, business leaders, and policy-makers. The author is certainly well qualified: Herb Weisberg graduated from Columbia University and received his doctorate in statistics from Harvard. After a brief stint in academia, he has spent the bulk of his career as a statistical consultant.

This book combines the history of a big idea, with a prescription for change. It is well illustrated and packed with original quotations. Extensive references are included.

I'd say it was suitable for an academic and specialist audience, and that university libraries would do well to stock it. The very well informed lay reader might have a crack at it, but this is no book for the statistical dilettante!
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By JuliaC VINE VOICE on 17 April 2015
Format: Paperback Vine Customer Review of Free Product ( What's this? )
This is a fascinating book about the theory of probability and how scientists have used statistical methods, and evolved their use over time to help their research. It's not really a book for the casually interested reader though, but would probably be very thought provoking for those who use research in their lives in a professional way. Herb Weisberg makes a strong case for the divisions between those who rely on quantitative and qualitative methodologies. There are a wealth of examples included in the book to back up his arguments. A great source of debate for academics.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 22 reviews
24 of 24 people found the following review helpful
Well worth the read for a lay person interested in modern day social and medical research. 16 Aug. 2014
By Peter F. Rousmaniere - Published on Amazon.com
Format: Paperback
Weisberg's new book is very valuable for any one who depends upon scientific literature and wants to find out how scientific research is what it is today: a mathematical exercise in which individual judgment appears to be banished. It is accessible to the lay person, with a few passages where one needs to work a little diligently. It's worth it.

I read the book in a pre-publication version. Also, I attended a presentation by the author before a group of non-statisticians interested. I am not statistically trained but need in my work as a journalist to consider a lot of evidence presented in a statistical context.

This book is something of a revelation. I'll go directly to the latter chapters that address the use of probability in social and medical research today. Weisberg describes how research as become the poorer for having lashed itself to proving statistical significance apart from the insights of content experts on the topic. It has frustrated me deeply how authors of papers will present their statistics-laden findings and then, it would appear, refuse to take the next reasonable step, and discuss the findings with content experts. As a journalist, I am amazed sometimes to find the authors of studies so remote from context in which their research takes place. As some one at the book group said, the appearance of science has been crowding out good science.

Research seems at times to have no expectation for how subject matter expertise fits into discovery, and odd state of affairs. I see this divorce acutely in research on the efficacy of spinal surgery; other readers will have their own choice example.

If you want to develop a perspective on the limitations as well as power of probability theory to be useful to solve real-world problems, this is likely the only book to help a lay person understand the situations today.

The earlier chapters of the book are charming narratives of the 10 to 20 notable contributors to probability and statistically-grounded research since the 17th C. One discovery for me was that the best minds in about 1700 were engaged in questions about how to assess the reliability of a finding that we are still asking. Weisberg does a pretty good job of describing how the modern world came to depend of a workable concept of probability.
24 of 24 people found the following review helpful
A History of the Concept of Probability, Leading to a Prescription for Improving Current Statistical Practice 8 Aug. 2014
By Michael B. Meyer - Published on Amazon.com
Format: Paperback Verified Purchase
This is an important, engaging and valuable book. It is sort of two books in one. The first part recounts the history of the concept of probability, as it evolved over time. This history starts with the Pascal/Fermat correspondence, continues through Bayes, Jacob Bernoulli, Laplace and many others, and concludes in the modern day with (among other things) the Pearson & Neymann versus Fisher disagreement and the frequentist/Bayesian disagreement. This history can be thought of as the story of how uncertainty was conceptualized as the idea of probability, and probability theory itself, developed. This history is written in an engaging manner, and in as clear terms as these somewhat difficult concepts permit.

The second part is quite different. Prescinding from the startling point made by Ionnadis and others, about the horrifying rates of non-reproducibility of behavioral science and biomedical science results, the author sets out one reason for this discouraging outcome: the narrowness of current statistical practice. That is, just get a P value of less than 0.05, declare that you are done, and quickly move on. The author is talking about the narrowness of statistics as it is actually practiced today by, say, behavioral scientists. This narrowness is odd when compared to the breadth of the available toolbox produced by the field of mathematical statistics. Further, this narrowness is not just odd; it probably contributes to the non-reproducibility problem. The author suggests ways to broaden current statistical practice to alleviate this serious problem.

Behavioral scientists and biomedical scientists could greatly benefit by analyzing the author's points. By any standard this is an excellent book.
9 of 9 people found the following review helpful
A shining gem 22 Nov. 2014
By judea pearl - Published on Amazon.com
Format: Paperback
The best book I found on the history of statistical ideas.
It is not about movements of university professors, nor about one proof or another,
but about the organic flow of core ideas from Cardan and Bernoulli to present day
thinking about uncertainty, its quantification and its management.
A sheer pleasure.
7 of 7 people found the following review helpful
A Revelation 25 Sept. 2014
By Lynne B. Hare, Ph.D. - Published on Amazon.com
Format: Paperback Verified Purchase
Willful Ignorance makes manifest the webs unintentionally woven by statistical practitioners to ensnare many technologies in mediocrity. With compelling clarity, Dr. Weisberg shows that blindly following main effect studies and relying on p-values alone have left many to wonder why they are not able to reproduce earlier results. The missing component is ambiguity, a fact that might easily be unrecognized had not Dr. Weisberg guided us back to the very foundations of probability as first considered in 17th Century dialogue between Pascal and Fermat and then modified through the succeeding centuries by great minds such as the Bernoullis, DeMoivre, Bayes, Price and LaPlace, then into the more modern era of statistical thinking through contributions of such notables as Keynes, Fisher, Gossett, Neyman and Pearson. The Fisher – Neyman-Pearson split, namely building knowledge from continual iterations between synthesis and analysis and making decisions based on the knowledge gained, as opposed to guiding decisions on the basis of p-values, is the major divide.

Intelligently researched and written, this book provides fundamentals of probability, its origins, its use and abuse. A careful reading can set us straight, remind us of our grounding, and force us to be more circumspect in our decision making.
3 of 3 people found the following review helpful
A terrific read that has changed the way I view the field of statistics 26 Nov. 2014
By Dave LeBlond - Published on Amazon.com
Format: Paperback Verified Purchase
I entered Chapter 1 of this book a confirmed Bayesian with my own preconceived notions about uncertainty. I exited chapter 12 somewhat embarrassed at my own naivety; wishing I could go back and edit passages I have written and presentations I have made over the years. I found the book very readable and filled with interesting new (to me) information about the elusive subject of uncertainty. Somehow Weisberg has made connections across many disciplines and provide a fresh perspective that should be required reading for every student, practitioner, or consumer of statistics.

I also found the issues raised in the book highly motivating. It has caused me to question the way I apply statistical tools in my own narrow field (pharmaceutical CMC drug product development). For instance: Should risk assessment (e.g. FMEA) use probability metrics for occurrence and detection? Should I be more careful in soliciting prior distributions? Is it possible or even useful to quantify model uncertainty? Do p-values really serve my clients' needs? Should I blindly apply fractional factorial main effect experimental designs or read up on more recent designs that permit estimation of interactions?

The history that Weisberg presents suggests (and I tend to agree) that we have made some wrong turns regarding the way we quantify uncertainty. I'm afraid... "... it will create much mischief before the mistake is recognized". (wish I could properly state & reference this quote). The suggestions he makes in chapter 12 are also recommended reading for government policy makers charged with the responsibility to make risk based decisions in the face of uncertainty in the interest of the public..
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