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
I'm an artist. I have always loved to read but work with my hands and eyes. I listen to books these days to get my fix and keep working.
Nate Silver guided me through the 2012 election with detailed analysis of the polling data he posted on his NYTimes blog 538. I was drawn to this book because I prefer his dry scientific reasoning, and how he explains his steps along the way.
In this book he talks about polling for elections, for which he has proven an expert and baseball statistics for which he designed a system a few years ago that gained him much fame and respect in the moneyball arena. He also describes in detail the successes and failures of several predictive techniques and reasons why humans are so bad at predicting the future. He describes why people continue to err factually even though we live in an information age. Namely, that there is too much data to gather without allowing our human subjectivity to taint the results.
This book does a good job giving insight into the difference between noise and signal and the value of being able to tell the difference