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  • Bernoulli's Fallacy

  • Statistical Illogic and the Crisis of Modern Science
  • By: Aubrey Clayton
  • Narrated by: Tim H. Dixon
  • Length: 15 hrs and 14 mins
  • 4.5 out of 5 stars (47 ratings)
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Bernoulli's Fallacy

By: Aubrey Clayton
Narrated by: Tim H. Dixon
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Summary

There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: It underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this same deeply rooted error shapes decisions in medicine, law, and public policy, with profound consequences. The foundation of the problem is a misunderstanding of probability and its role in making inferences from observations.

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it. He highlights how influential 19th- and 20th-century figures developed a statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics.

Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for listeners interested in the statistical methods that frame our understanding of the world. He contends that we need to take a Bayesian approach - that is, to incorporate prior knowledge when reasoning with incomplete information - in order to resolve the crisis. Ranging across math, philosophy, and culture, Bernoulli’s Fallacy explains why something has gone wrong with how we use data - and how to fix it. 

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.  

©2021 Aubrey Clayton (P)2021 Audible, Inc.

What listeners say about Bernoulli's Fallacy

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    4 out of 5 stars

Great take on the troubles with frequentism

Very interesting dive into the limitations of the frequentist approach!

Narrator absolutely understood the brief and was able to convey the book's statistical concepts in an engaging and entertaining way (as I'm sure the author had intended).

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Full of stories and bizarre histories

Shakespeare, were he alive today, might say 'Zounds, I was never so bethumped by statistics.' and many of us feel the same. Why are the definitions so convoluted that the best of us easily end up confused and are misled, sometimes by ourselves?

Clayton tells the story of why it is (worth reading for that alone, a clue is that one pioneer was Professor of Eugenics, a chair funded by an endowment from another pioneer ), he explains clearly why it shouldn't be so, and why it matters to all who care about science that we change our statistics, now.

You don't need maths to follow his prose- and let's face it, how many of us ever come close to really understanding the maths of the 'normal curve' and yet we use it over and over.

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this book should be mandatory in school

the unique perspective offered by this reveals a vast chasm between our methods of doing science and a reasonable approach to hunt for the truth! EVERYONE should know this. EVERYONE....

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Hard to follow. Essential to know.

This was incredibly difficult to follow. The subtleties and explanations are mind bendingly difficult to fully grasp. Does not lend itself well to an audio book. But the subject matter is essential knowledge.

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Gripping

I have given a rating for the story as well as the performance because this book reads like a mathematical "whodunnit". I read this against the background of having a maths degree (which included several modules on probability and statistics) together with a diploma in statistics, a professional life (now retired) in medicine dealing with the uncertainties of diagnosing diseases and interacting with coroners who draw conclusions about causes of death, and limited published work of my own. This book summarised very clearly for me my long held reservations about the place of statistics in these fields. So much of a career in medicine involves pressure to produce publications, which are often set against incomplete understanding of a small corner of statistical theory embraced for expedience to get the publication finished. In fact, it worried me so much that I took a maths degree with statistical modules in an attempt to reassure me of the validity of what passes for objectivity in medicine---it did not and now this book explains why. It was interesting to learn about the private agendas of the more famous frequentists and how this suited the political climate at the time. It is frightening to observe how regulatory bodies appear to use dubious statistical methods to claim objectivity in their seemingly tyrannical hold over those they regulate. It is sobering to speculate on their level of understanding of the statistical methods they use, let alone their insight into the problems associated with them, as so eloquently and clearly expounded in this book. This should be essential reading for politicians and regulators as much as for scientists and mathematicians. I don't imagine that will happen while the current flawed methods suit their political agendas (in the same way that they did for the founding fathers of frequentism).

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Perhaps one of the most important books of my career as a DS

I was interested in Bayesian methods before but now I realise that this interest is not some pet project but a tool that I must become familiar with. I’m now not just a Bayesian, I’m an anti-frequentist.

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Learnt loads + eye-opening & fascinating history

Fantastic book. I've studied stats on and off for 5 years, and this book weaved everything together and gave so much more - learnt a lot about (frequentist) statistics, the philosophy of inference and the eye-opening history of statistics. If anything, it could have done with talking about Bayesian statistics more..!

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Excellent, required reading for anyone who makes inferences from data, which is everyone!

Not only is the book incredibly thoroughly researched and evidenced, it’s presented in an easily accessible manner for non experts. The narrator does a perfect job too.

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1 person found this helpful