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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
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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

3.56 of 5 stars 3.56  ·  rating details  ·  668 ratings  ·  131 reviews
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, Sharon Bertsch McGrayne explo ...more
ebook, 335 pages
Published May 17th 2011 by Yale University Press (first published May 14th 2011)
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If only I had known how to use Bayesian probabilities before reading this book I could have taken the probability of my liking a book well received in a NY Times Book Review as my prior, plugged that in to a Bayesian calculation as to whether or not I would like this book, and quickly would have come up with the answer "highly unlikely" and saved myself a few hours of my life.

According to the author, Bayes' rule is the greatest mathematical equation/formula/thought process in the history of hist
I think this is the first book about Bayes' theorem and its applications, for the general reader. The book does not explicitly state the theorem as a mathematical formula, until the second appendix. However, the general idea is described, as well the general ideas behind it. The history of the theorem is described in some detail.

The ebb and flow in belief in the theorem over the course of 150 years is interesting. Applying Bayes theorem requires a prior probability, and this is often poorly know
As someone who actually works with Bayesian methods, I was very much looking forward to reading this book. The strange history of Bayes' Theorem had been briefly mentioned in other, more technical books I had read. I finally wanted to get the whole story.

Alas, that story, at least as presented in this book, turned out to be not quite so exciting. Except for the insights into Laplace's involvement, and in particular the interesting sections on Alan Turing's work, I found this to be a rather lifel
Dennis Boccippio
It probably takes a special sort of person to dive into an entire book about one statistical theory, but for those so-motivated, this one pays off.

The pro's: The author has done a phenomenal job at capturing and richly detailing the very "large" personalities that have championed (or condemned) the use of Bayes' Rule through the centuries, amidst a little-known and long-simmering war that has persisted between statistical Bayesians and frequentists since the concept was first brought forward. T

Bayes' Rule is a mathematical formula that allows one to calculate a conditional probability (such as the probability that a woman has breast cancer given that she has a postive mammogram). It has many useful attributes, such as allowing one to updates ones estimates of a probability as you obtain new information, and can be adapted to deal with such basically non-numerical forms of information as expert opinion. One can also use it to estimate the probability of events that have not happened,

Rafael Maia
I wish I had liked this book more than I actually did. Most of the stories reported are very interesting and entertaining, reflecting how academics have been fiercely debating conceptual aspects of Bayes theorem, as well as the bayesian-frequentist feud, while at the same time it was being successfully applied in many crucial issues such as finding stray atomic weapons and linking smoking to lung cancer.

However, I did not find this book well-written at all. It's just not an exciting read - and i
AJ Armstrong
First, a cachet: unless you are already interested in one or more of Statistics, Decision Theory, Machine Learning, or the history and philosophy of Science and Mathematics, you are probably not a member of this book's audience. However, if you are, you will find a meticulously researched, erudite, and detailed survey of the history of statistics and decision theory. Undergraduate level familiarity with statistics and a generalist understanding of Bayes' rule would be very helpful but not critic ...more
A friend recently pointed out that the term 'Bayesian' is now entering the common parlance such that the NY Times can use it in an article without explanation. This would come as a huge surprise and disappointment to many statisticians from the early part of the 20th century, when Bayesian was a bad word and the theory was largely refuted. Why would a statistical theory be so upsetting, you might ask...well, McGrayne's book explains why, and gives the history of the theory over time and how it m ...more
Apr 19, 2014 Ms.pegasus rated it 3 of 5 stars  ·  review of another edition
Recommends it for: anyone who has read the Nate Silver book SIGNAL AND THE NOISE
Recommended to Ms.pegasus by: citation if Nathan Silver's book
Shelves: nonfiction, history
As the subtitle proclaims, this book chronicles the history of science It also demonstrates how a simple formula evolved into a sophisticated application that required the invention of high speed computers to exploit its potential for prediction. It complements the information in Nate Silver's book, THE SIGNAL AND THE NOISE.

McGrayne introduces the reader to Bayes's Theorem with the proposal that given the unknown position of a billiard ball, its probable position can be narrowed by collecting da
It is the third book I read about statistics in a short while and it is probably the strangest. After my dear Taleb and his The Black Swan, after the more classical "Naked Statistics: Stripping the Dread from the Data", here is the history of the Bayesian statistics. If you do not know about Bayes, let me just add that I like the beautiful and symmetric formula: [According to wikipedia] For proposition A and evidence B, P(A|B) P(B) = P(B|A) P(A) with P(A), the prior, is the initial degree of bel ...more
I liked this book a lot more than I thought I would, particularly given its ratings. This is a non-technical history of the use of Bayesian statistics. The book is so non-technical that no background in statistics is really required at all. The non-technical nature also comes at the cost of a lack of detail. The book only explains WHY Bayesian methods were so poorly thought of for years at a very high level, without enough detail to really understand the underlying issues. In addition, its descr ...more
Rajesh Israni
My following review on "The Theory That would Not Die" is not just a review of the book, but also a detailed account of the actual Bayesian theory and its numerous benefits that unfortunately still remain hidden from general public. I hope that by sharing the importance of this great piece of theory it might kindle your interest to learn more and read this delightful book by Sharon Bertsch McGrayne. To understand the importance and the concept of Bayes Theorem it’s important to establish its nee ...more
The basic idea of Bayes' Rule is that you treat probability as a degree of belief (i.e. how much are you willing to bet on something) instead of a relative frequency (i.e. count the number of royal flushes out of all possible poker hands).

Bayes' Rule allows you to "learn" by updating your (prior) degree of belief of something (i.e. probability of finding a sunken ship in a certain part of the ocean) given new information (i.e. a captain's log) in order to obtain knowledge in a "posterior" belie
Bob Stocker
Because I had read several GoodReads reviews of The Theory That Would Not Die by Sharon Bertsch McGrayne, I knew that it was not an introduction to Bayesian statistics. I was still sufficiently intrigued by the subtitle How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy to take it out of the library. The book had lots of “who,” “what,” “when,” and “where,” but almost no “how.” I left with a knowledge who applied Bayes ...more
There is some very important information here but it is buried under a giant pile of whocares?.

By giving us the life of Bayes, the childhood of Laplace , ... , I think the author is trying to force the book to have a narrative, but I doubt that many people buying books about mathematical theories are interested in the minor details of the mathematicians' lives. This type of writing would be bad enough if the importance of Bayesian analysis were clearly explained, but it isn't. For instance, in
Seth D Michaels
Complex and brainy, but very interesting; I think it's the best you can do at explaining what Bayes' rule is to non-specialists like me. With an admirable minimum of equations, McGrayne talks about the origin of the Bayes statistical method, the controversies around it, and its wide range of applications. I almost wish I could give it something more like 3 1/2 stars, because I feel like I should have come away from the book with a better ability to explain exactly what Bayes' rule is, rather tha ...more
I really wanted to like this book more than I did. The first three chapters are particularly frustrating -- I got the feeling that the author knew much more than she dared to say in a popular book and figuring out exactly what Bayes and Laplace did was not easy. The rest of the book, which consists primarily of descriptions of how Bayes' Rule has been applied, is much better. In particular, the chapters on how Bayesian methods were used to crack the Enigma code and find missing submarines were i ...more
Covers the history of Bayes' rule but there's little on actual mathematical application. The book was heavy on mathematician drama and light on data-driven aha! moments. If you are interested mainly in History of Mathematics, raise this review to 3.5 stars. But the book's subtitle is misleading: rather than "_how_ Bayes' rule cracked the Enigma code..." it should read "_that_ Bayes' rule cracked the Enigma code..." since there's little "how" to be had. An interesting piece of history, but ultima ...more
Aug 11, 2015 Thomas rated it 2 of 5 stars  ·  review of another edition
Recommended to Thomas by: Ken Harrison
Shelves: science, history
I'd say this is a good example of what can go wrong with a whirlwind tour. I never got a very good handle on any of the specific problems, or even the application of Bayes' rule itself. I read this in part because I work in a field where the ability to do Bayesian statistics might be useful. Unfortunately, I'm not much closer to that. I did like the problems in the appendix (and found them helpful in understanding), but I doubt that they are very representative of modern applications.
Excellent and very readable book about the history of Bayes' theorem. I never realized that Bayesian statistics, one of the cornerstones of modern data science, had such a turbulent history--so turbulent that, during the cold war, being called a "bayesian" was tantamount to being called a Communist.

If you're at all interested in the history of mathematics, this is a surprisingly exciting story. I expected a rather dull and academic history; that is NOT what this book is.
It feels strange to hear Bayes' approach to statistics constantly referred to as a theorem, because as presented here it seems much more like a methodology. Essentially, a Bayesian approach is about establishing an initial assessment of likely probability and then refining it over time with additional information. There's clearly some skepticism that comes in if you can't make your initial prior estimate too informed and start with a blind guess of 50-50, but as a general approach it doesn't see ...more
John Esterly
I enjoyed this book as a history of the application of Bayesian statistical analysis and theory. More than anything, it served as a 250-page must read list for future reading. This book was much less technical than it could have been, focusing more on the history of Bayesian theory, from Bayes himself and near-contemporary Laplace, through early use in the code-breaking efforts of World Wars I and II, into modern times using computer technology. McGrayne highlights the achievements and contribut ...more
Herbert Weisberg
I imagine that Bayes must be turning over in his grave. The good reverend was a deep philosophical thinker, and this popular exposition caricatures what and why his famous rule was created. It has been said that there are many kinds of Bayesians. The book oversimpifies the situation and various points of view in many ways. In particular, it fails to distinguish Bayes's Rule as a mathematical (and quite trivial) truism and the various applications to which the Rule has been put. It is the latter ...more
Bill Leach
Interesting book in terms of the portrayal of the history of Bayesian methods. Good descriptions of the persons involved.

While the author describes many applications of Bayesian methods to problems in a variety of fields, no detail is provided as to the basis of the prior knowledge nor the nature of the incremental knowledge that was used to update the priors.

An example of the Bayesian view of breast cancer testing is provided in a short appendix.

The intended audience of the book is not clear. I
Sachintha Karunaratne
Author has put a lot of effort to gather all the historical background covered in the book.
I did enjoy some chapters significantly more than the others. Though the book is aimed at
the general public interested in science (not necessarily trained in Bayesian statistics), I believe
that having experience in Bayesian statistics does make the book more enjoyable, which is of course
not surprising. I would have preferred if the author had been more relaxed in terms of some of the vocabulary
she used; i
T.M. Mullin
Statistics, history, philosophy and academic politics; what more could a nerd want? Laplace is my hero. Bayes Rule is a very different way to think about problems. P(A|B)=[P(B|A)P(A)]/P(B)
This was a book that I wanted to like more than I did. The history and rise of Bayesian statistics from humble origins is an interesting one and well captured by this book in places. There are many fascinating vignettes on the application of Bayesian theorem in military and commercial areas in this book, but little overarching narrative to weave them together into a page turner. Though I learnt a lot about the history of Bayes theorem, this wasn't an altogether easy read. If you use Bayesian sta ...more
It's a pretty good history of Bayesian statistic, giving a good overview of the reasons why people are excited about it. Perhaps overly enthusiastic, both exaggerating the differences to other types of statistical reasoning and never making it entirely clear what distinguishes Bayesian from frequentist approaches, nor indeed what statistical reasoning is about to begin with.
But then, I came into statistics when the Bayesian-frequentist wars were only a distant echo, so maybe these antitheses are
Chad Miller
I don't read a lot of nonfiction. I think it's because it often falls into the problem this book has. That is, there's a morsel of good story, but it's not enough to fill a book.

It's interesting that Bayes' Theorem wasn't accepted at first, and why, and how it languished in obscurity until proving its worth, and being a secret weapon, of sorts, of the US against the Russians. But that's maybe half the book, and the rest just isn't very interesting.

Being constrained to real history hinders the bo
Too much biography, not enough mathematics.
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