The Theory That Would Not Die

How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy

De: Sharon Bertsch McGrayne

Narrado por: Laural Merlington

Duración: 11 h y 51 m

Resumen del Editor

Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.

In the first-ever account of Bayes' rule for general readers and listeners, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years - at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information, even breaking Germany's Enigma code during World War II, and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA decoding to Homeland Security.

Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

©2011 Sharon Bertsch McGrayne (P)2012 Tantor

Reseñas de la Crítica

"If you are not thinking like a Bayesian, perhaps you should be." ( New York Times Book Review)

A fascinating story

The history of Bayesian statistics is fascinating, and this book ably tells the story of its twists and turns. I can understand why the author wants to insulate the reader from the mathematics, but I would have preferred a little more technical detail, especially as it applies to numerical methods. You'll come away from this book understanding how useful Bayesian inference is, but you probably won't learn very much about how it works.

I had no trouble understanding the narrator, but this is the first audiobook I've listened to in which some proper names (especially French names) were horribly mispronounced.

Amazing story

Even though I have used statistics in my work, this thoroughly researched book opened my eyes to the power of probability and statistics.
I am inspired to learn more about Bayesian and Pascal’s work

I don't get the bad reviews...

Plain and simple, if you want to learn the intricacies of Bayes Theorem please go to a textbook, there are 100's of them out there. This book was written by a journalist on the history and important events that led to the rebirth of Bayes on the 20th century. If you're familiar with Bayes, this book for sure will give you a new perspective on the topic.

educational, curious

wonderful story lines building on logic and usage of probability and its two main philosophies. a good read.

A nontechnical math history

The author of a book like this has to decide how technical to get. McGrayne has opted for extremely nontechnical. Unfortunately, this turns much of the book into a soap opera. There are Designated Villains (establishment types who want to keep doing things the old way), then along come Valiant Heroes (rebels who use Bayes), the Valiant Heroes solve a problem that no one else had solved – then on to the next chapter and the next problem, same story. The book is weak on explaining the math of why, on this or that particular problem, one method worked better. It’s much more informative about the individuals on both sides and about the circumstances of their conflicts.

Unless you’re already completely familiar with the math, I recommend beginning at the end – with the case study in Appendix B (Chapter 24 in the audiobook). According to the author’s numbers, if a woman in her 40s has breast cancer, the chance that she will get a positive mammogram result is about 80%. Nevertheless, if a woman in her 40s gets a positive mammogram result, the chance that she actually has breast cancer is only 3%. Why are the numbers so different? Bayes’s theorem explains how to solve problems like this. In Appendix B, the author works through the application of the theorem to this specific situation, in a way that greatly illuminates the theorem. It makes the rest of the book somewhat more comprehensible.

Very informative and captivating

Not what you’d expect from a book on a statistics theory. It was much better.

The Story Behind Bayes Theorem (Rule)

If you’re looking to learn about how to use Bayes Theorem (Rule) or learn about the components of the formula and why it’s built the way it is and how it actually works, this is NOT the book for you. If you want to learn about the history behind it, who invented it, who added to the invention, how it survived in the shadows for centuries before becoming a foundational asset to the field of probability, then you found the perfect book. I’m in no way belittling this book by saying this I’m merely stating that this is a history book not a math book. I’d like to add that learning the history of Bayes Theorem (Rule) is vital to understanding the magnitude of what this formula provides to the user. It’s a very motivating and uplifting story that shows the light at the end of the tunnel to people new to learning Bayes Theorem (Rule). We get a glimpse at its potential to make world changing revelations.

Thorough history

This book is an indepth history of the theory and its broad applications. Great base to begin study from

interesting history

bayes' theorem had a surprisingly tortured history. I always considered it a useful tool in a data analyst's bag. it never occurred to me that some would become so religious about its application to statistics.

great

Or one of Laplace's most potent contributions to science!

I found the narrative engaging and at times gripping. Sometimes the repetitive use of examples litter the historical story line, but the story itself is illuminating.

I've never heard as much info on RenTech, which was fascinating, but wish more time had been spent on Mercer.

great listen, great read