Nate Silver isn't an expert on statistics. As he explains himself in the book, he's an enthusiast who happened to strike gold when he applied statistics to fields where the competition was very weak. Silver's lack of expertise is very much in evidence throughout the book, in the form of two flaws: shallowness and inaccuracy.
Let's start with the shallowness. Most of the book is taken up by descriptions of various fields where statistical prediction has been applied with differing degrees of success: earthquakes, weather, politics, sports, and so on. The main point of these sections seems to be that pure statistics isn't enough -- you need specific knowledge of the problem in order to make predictions. That's a good point, though fairly obvious; to illustrate it, much time is spent simply describing these various fields. We get a description of how contracts work in baseball, a taxonomy of types of poker player, some information on the planning stages of the 9/11 attacks, and more.
Silver doesn't know very much about any of these subjects, so the result is a shallow and unfocused collection of trivia. Worse still, Silver's knowledge of statistics -- the subject of the book -- isn't very good either, so that topic gets a similarly vague treatment.
Worse still is the inaccuracy that plagues the book. I can't speak for the sections on baseball or terrorism, but I noticed many glaring flaws in the explanations of statistics. One important mistake is the treatment of the concept of bias. Bias is an important technical term in statistics, but Silver talks about it as though he were using the colloquial usage, in which bias is always a bad thing to be eliminated. In fact, bias is often useful and important in solving practical problems in statistics.
Another, particularly annoying mistake was the description of David Hume's ideas about induction. Silver insultingly claims that Hume's idea was that if a claim is not known with 100% certainty, it is a mistake to give it anything other than a 50% chance. This is obviously nonsense and unrelated to Hume's actual thoughts, which should have been given a much more thorough treatment if they were to be mentioned at all.
Despite all this, it's a reasonably entertaining book, and the narrator does an excellent job. But I wouldn't recommend it if your goal is to finish the book knowing more than you did when you picked it up.
A good defense of general skepticism and accessible explanation of the usefulness and limits of forecasting.
Money ball and similar books by Michael Lewis for making data analysis accessible.
Unintentionally hilarious name-dropping which I found more endearing than annoying. Almost like somebody told Mr. Silver to punch it up. Lots of clangingly unnecessary references to the food eaten with smart, successful people. Small price to pay for this book,though.
people interested to hear about past events but not necessarily in a fun or entertaining manner
No, but it did turn me off from this writer
Very long details about historical events and how people failed in predicting them, which is quite obvious, since if those events were predicted they wouldn't have happened. It's good Audible has 2X speed so I was able to reduce my time wasted listening to this book. In short it's a book that has no added value whatsoever.
Nate explains things very well. Easy to listen to and you will learn a lot. You don't have to know math to enjoy this book.
Maybe - I don't tend to read books over and over again.
Not sure - he was a good narrator though.
Bayesian thinking. I've been familiar with Bayesian mathematics for a while but I'd never quite thought about applying it to probabilistic thinking the way Nate discusses it.
This book was an amazing read. Nate uses lots of great examples from a wide-variety of disciplines and professions to show the usefulness and limitations of statistics and prediction models.
This book emphasizes how data should be addressed as the title says. Distinguishing between the signal and the noise that comes along. Though the author involves many endless examples along his personal interest, not many gives concise illustration of how interpretations should be made and how people failed in avoiding them. The poker, baseball, basketball, weather, and other topics give little or no insight on what the reader should be doing, which is not productive after 15+ hours of listening.
Through different disciplines, the author explores how statistics can inform. It's not told in "geek speak", rather in everyday, intelligent stories. And, as happens in academia, it cautions about listening to the noise of information instead of seeing what's truly informative.
Nate Silver's book jumps underlying topics casually (baseball stats, gambling, weather patterns, natural disasters) and uses the science of prediction as a throughline. This creates a little cognitive noise in its own signal. Other than that, it's a good, armchair introduction to the science of Bayesian statistical methods.
nate silver is the son of a michigan state professor
his careers in poker, finance, and baseball proved unfulfilling
i suspect the wolf of insignificance was nagging at his door
he needed a new and meaningful focus for his considerable intellect
he now aspires to be the high priest for our digital and data-driven age
the wise sorter of signal & noise / truth & lie / wheat & chaff
the book isn't entertaining because nate silver isn't entertaining
he wants to tell you the truth and show you how to recognize a lie
he then applies his focus and filter to the ocean of data we swim in
at heart, the book is a sturdy compass and a very necessary tool
we live in an expanding jungle of useless and biased information
nate silver wants to lead us to the promised land of the true signal
Soo Lee Davis
Yes - profound lessons in how to think and solve problems
Thinking like a fox.
A hint at humor.
So many! Must read again