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 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. …
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 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 de-coding 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. - Publisher.
Review of 'The Theory That Would Not Die' on 'Goodreads'
3 stars
Bayes theory is cute. Pop nonfiction math books seem incapable of being patronizing on one extreme or invoking their math theorem as an abstract magical spell on the other. I prefer the later, which is what this is. How did we find Russian submarines? We cast Bayes at them. Sometimes, even as someone very familiar with Bayes theorem I found these invocations impossible to understand what was literally happening, but overall, this is an easy and mathy read. 3.5 stars.
Review of 'The Theory That Would Not Die' on 'Goodreads'
3 stars
If you are interested in learning about actually using and get a deeper understanding in bayesian statistics: read another book, this will not help you with this.
But the book gives a great history on Bayesian Statistics from it's beginnings, the Bayesian vs Frequentists-wars and it's triumph in our computerised world. So if you want to learn about this, you'll have a fun time reading it.
