A guide to logical thinking and alalysis of data that should be required reading for everyone. Covers somewhat different territory from that first plowed by Freakonomics and Super Freakonomics, but just as insightful.
I am a documentary film producer from Los Angeles.
While missing the point.
This book is very hard to follow. It feels like there is not enough material and the author is blowing time and filling pages with useless details.
I'd rather go for something by Michael Lewis or Malcom Gladwell
I'm Trying to see the world with my ears.
.....Nate Silver is the wunderkind who burst onto the scene with his blog that supplied intellectual elbow grease to issues of probability analysis . In his new book he wanders like a modern day Socrates searching for those with true wisdom . And he finds it--among modest , hardworking , humble folks across an array of industries and government institutions . A wonderful read.
Definitely a must read or listen for anyone that is concerned about what so called experts are saying. We all need to be wary of predictions and statistics especially in the hands of governments and corporations. This is an excellent primer on the topic.
I lined this book. The author highlights the issues of predictions and forecasts in plain language. The examples are relevant and interesting.
This book was an interesting account of the natural limits and underlying processes of human thinking, technology, and how they are used in prediction. If the phrase "big data" annoys you, this book may provide a refuge from misinformed consensus views of problem solving. Mike Chamberlain did a fantastic job narrating this piece, which was likely made easier because the writing and themes of the book were so captivating. After listening to this book, I must admit my views are heavily biased due to the value I place on prediction.
The book is a little dry. I was hoping for something more in the realm of freakonmics or Blink, but, the information was good. It took me a long time to finish, which is my key indicator for whether the book was good. If you're into data, I would encourage you to check this one out, but otherwise, I'd stay clear.
Very informative but needs to be rewritten to reach a wider audience (partially attentive people). Examples given in certain circumstances like the actual scientists' names such as ones that either proved right or wrong with their theories evoke human interest and makes it easier to absorb the material presented. The book is politically unbiased which is what will make is truly relevant in the long run. Might be considered a classic in the years to come if rewritten for different audiences.
Struggled to finish it, was too long for the ultimate takeaway of the book. Still an excellent overview of data analysis and predictions.