The Signal and the Noise #3

I really enjoyed completing this book. This book, was much more than an enjoyable read, but something I learned a lot from and can apply this information to my life when I am put in a scenario when I have to make prediction. As I had mention in my previous blogs about this book, the purpose of this book is to inform the readers on how to distinguish useful information (the signal) between the distracting information (the noise) in order to make more accurate predictions. Nate Silver, the author, uses each chapter as a new strategy when predicting and then proceeds to give either a personal anecdote, such as with his chapter about the poker bubble, or a popular issue today, like his chapter Rage Against the Machine, which examines Artificial Intelligence in technology today, and how that effects their predictions.

This has been my favorite book so far in this reader’s workshop.  I particularly enjoyed how Silver uses very topical issues to analyze. My favorite part of the second half of the book was his analysis of technology and human nature or your “gut” feeling and how these two opposites play a role in the prediction. He concludes that both play a significant role in an attempt to predicting an outcome or result. His main examples were two that I recognized, the story of a Lakers fan and Deep Blue. He talked about how a fan, trusted his gut, which was telling him that the Lakers were going to win the NBA championship, despite the 6.5-1 odds against him. The fan’s reasoning behind this was that the Lakers were lacking chemistry, which no statistic has found out how to measure accurately, and that was the reasoning for their slow start. The fan trusted his gut, bet his life savings on the Lakers winning the championship, and won half a million dollars. Silver explained that the fan had though the Lakers odds were better than 1 in 6, and the fan had said he though there odds were about 1-4. Silver introduced a formula he uses for predictions, which he explains in reference to the Laker’s fan’s bet on page 238, “The theoretical profit of the bet was $70,000 dollars, and that consisted of a 25 percent chance of winning 520,000 and a 75 percent chance of losing 80,000 averaged together.”

Outcome	Probability	Net Profit
Lakers Win Championship	25%	520,000
Lakers Do Not Win Championship	75%	-80,000
Expected Profit		70,000

When putting predictions into this formula, it is obvious to see why this was a smart prediction   The same fan also placed several bets on the Cleveland Cavaliers scoring more points in their game than expected. His reasoning behind this was because their point guard was a free agent next year and would try harder, and also play at a quicker pace so they could more possessions, which would therefore increase his stats that season.

 On the other hand there was Deep Blue. Deep Blue was a chess machine that was designed by IBM which used statistics to determine which move had the greatest probability of guaranteeing a win. He said how both  of these are in some way successful, they both have their faults, as the Lakers fan only won about 58% of his bets. Deep Blue had also lost to Grandmaster in chess, when the grandmaster, Garry Kasparov, did as Silver explained on page 271, “Kasparov had taken the database out after just three moves. As we have learned throughout this book, purely statistical approaches toward forecasting are ineffective.”  I thought that this part can be applied to life in many scenarios in life and will therefore be very useful.

I would recommend this book to anyone, before reading I would advise having some knowledge about the economy in this decade, especially in the recent recession, as multiple chapters in this book are devoted to uncovering the reasons why no one was able to predict the recession. This is a book that you can truly learn something from that will benefit you later in life, which is why I think everyone should read it.