Thought provoking as you listen to pundits and realize they don't really know what they are forecast or predicting.
The author used is money ball type experience and brings that analysis to examples range from politics to weather to hurricanes and earthquakes.
boring - or a documentary ;)
Web Developer, Eldoren Design, www.eldoren.com
This was a great book, loved the discussions on baseball, odds and the many topics the author covers. Its a very hard book to describe though. I never got bored and every chapter offered me something new and fresh. Be a great book for anyone in marketing or SEO. I would recommend it. Worth the money.
There is a lot of background material that goes over prediction for climate change, stock market and terrorism which is okay but the real mechanics of bayes is really only a small portion of the book.
There are other books that cover bayes in more in depth so that's fine but it felt like 75% of the book was talking about backgrounds that really what you can do step by step to do better.
Maybe if I didnt get the unabridged version, it might have been more concise to what I was looking for.
People who need to know why making predictions is difficult.
Write more about how to make a good prediction - what works?
It didn't really answer the second part of the question: "and some don't".
Then you would have this book. The anecdotes are well told, but there is nothing revolutionary in this book. Nate Silver just reminds us of how bad humans are at just roughly figuring out statistics, then roughly tells you how to get better at forecasting and making predictions. My advice: Read the wikipedia page on Bayes' Theorem and read Thinking, Fast and Slow by Daniel Kahneman. You will have a better time.
bayesian statistical predictions.
I am being forced to write additional words to meet a 15 word minimum even though I was asked to sum up the book in 3 words
just read it. it's fun for all ages!
I would never sit long enough to read this book in print. It is very "dense" with information and statistics, which it should be because it is a book about statistics, but for the casual or business reader, there is just too much detailed information. It really would have been better as separate books on each topic. If you use statistics for a living, this is a must read.
The most interesting idea was that most studies report erroneous results and no one calls them on it or reports the errors, meaning that most of what we KNOW to be true, isn't. Bayesian analysis was very interesting and useful. Would have liked more information on how to apply it to everyday life and business situations.
Nate does what no one else has managed to do. Write a comprehensive book about statistics and probability that is interesting and informative. I loved listening to this book.
I enjoyed this book, but I'm a bit of a numbers junkie myself. Silver does a great job of explaining complicated subjects in plain English--good enough to make best-seller lists. He explains predictions for politics, weather, baseball, poker, economics including the stock market, earthquakes, global climate change, and terrorism. He ties this together with Bayesian statistics. He describes this in terms that anyone can apply. Along the way he explains over fitting and under fitting of models. He describes the advantages of models based on physical principles. I enjoyed the way he used betting terms (hedgehog and fox) to describe political pundits. I would make this book required reading for a statistics class. It won't thrill everyone, but anyone who is curious about predictions will enjoy it.
This book is exactly what you'd expect based on the title. An explanation of what is involved in statistical modeling, along with real examples of what causes a prediction to fail, as well as what helps a predictive model to be more accurate.
I have a fair amount of training in the hypothesis testing school of statistics, but am far less experienced with modeling. I appreciate the criticism Nate has for hypothesis testing, and found his explanation of "over modeling" to be particularly edifying. I'd suggest this book to anyone that has any desire to understand the modeling process, or to understand why certain modeling efforts are so fruitless (Earthquake, Economics, Etc.).