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.).
Like lots of people, I followed online for two election cycles and came to believe that Nate had the best methods for election prediction. Because of that history, I was very interested in this book when it came out. While there was a lot of interesting information in the book, quite a bit of time is spent on Poker, the way he made a living for several years. Not knowing Poker, those sections were not meaningful to me. His analysis of baseball, another area where he did statistical work, was interesting to me although others may not care about it. The discussions of politics were also interesting to me but they were shorter than I expected. Overall, it's pretty good but no more illuminating than other well know books on prediction that you can find on Audible.
I was hoping for something more from the famous Nate Silver. If you have had a sophomore statistics class, then you won't find anything new here. I don't understand why this book gets such good reviews. It's not a bad book, but it's not ground breaking either.
Probably miss out on the charts and illustrations which I presume are in book
If you liked Freakonomics or any of Gladwell's books then you will love this analysis
Data science for dummies.
A very entertaining intro for those of us who aren't techno-current. Lots of different fields of enquiry used for examples. Enough of the author's personality to keep it lively.
Fun for all --
It's always refreshing to read a different way to tell the same stories. This book is a must read for anyone, absolutely anyone, that wants to have a better grasp of what it perceives as real.