Standard Deviations

Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics

De: Gary Smith

Narrado por: Tim Andres Pabon

Did you know that baseball players whose names begin with the letter "D" are more likely to die young? Or that Asian Americans are most susceptible to heart attacks on the fourth day of the month? Or that drinking a full pot of coffee every morning will add years to your life, but one cup a day increases the risk of pancreatic cancer? All of these "facts" have been argued with a straight face by credentialed researchers and backed up with reams of data and convincing statistics.

As Nobel Prize-winning economist Ronald Coase once cynically observed, "If you torture data long enough, it will confess." Lying with statistics is a time-honored con. In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpot theories. Sometimes, the unscrupulous deliberately try to mislead us. Other times, the well-intentioned are blissfully unaware of the mischief they are committing. Today, data is so plentiful that researchers spend precious little time distinguishing between good, meaningful indicators and total rubbish. Not only do others use data to fool us, we fool ourselves.

With the breakout success of Nate Silver's The Signal and the Noise, the once humdrum subject of statistics has never been hotter. Drawing on breakthrough research in behavioral economics by luminaries like Daniel Kahneman and Dan Ariely and taking to task some of the conclusions of Freakonomics author Steven D. Levitt, Standard Deviations demystifies the science behind statistics and makes it easy to spot the fraud all around.

©2015 Gary Smith (P)2016 Gildan Media LLC

Reseñas de la Crítica

"A very entertaining book about a very serious problem. We deceive ourselves all the time with statistics, and it is time we wised up." (Robert J. Shiller, winner of the Nobel Prize in Economics)

Excellent

This book should be a must read for every student who wants to have a sound career in behavioral sciences.

Great examples of failing to understand methodology and lying with stats.

This book will help you become a skeptical consumer of stats and the conclusions drawn from them.

Rehash with a few highlights

These books all have the same paradoxes and mistakes. That said there were a few new nuggets here.

Adorable!

I love love love this book! I have recently started a Data Analytics course and this book is perfect to listen to in my free time and still be about my course. I did not like, though, that the audiobook makes refferences to diagrams that are nowhere. This book does not have an accompanying PDF, so it was a little annoying. Also, the pause between subchapters is way too long, in my opinion. Otherwise it would have been 10 out of 10.

Good Introduction on Misinterpretation of Data

The book provides an excellent introduction on the misinterpretation/misuse of data and statistics. For example, it is often cited that college graduates earn more money than high school graduates. But the fallacy of that thinking is that college graduates are self-selected; they choose to attend college and so the difference isn't just having a college degree (which result in a higher compensation). After all, billionaires like Bill Gates, Steve Jobs, and Mark Zuckerberg became rich despite not having a college degree (quite big exceptions to that statement). The book included some cautionary tales to illustrate a point but wasn't related to data. For example, the book described how Sir Arthur Conan Doyle (author of the Sherlock Holmes stories) believed in paranormal activity despite his friends' explanation on how the scams worked. Eventually, that transitioned to studies into paranormal activity and how researchers cherry picked the data that supported the theory and "explained away" the data that didn't support it.

Great eye opening book! Made me think on my future

Great eye opening book! Made me think on my future research. Thank you for your insights.

Good read for all empiricist

I have a MSc in statistics, and I have seen countless examples of miss-used statistics in medicine and economics. This book offers a great overview of the most common pitfalls, including several examples of each.

Must Read

Great book that makes forces you to be more critical about how you think and what we base our beliefs on. Everyone can benefit from reading it:

Good but stumbles on macro economics

Very good read and certainly recommendable. Just ignore the "USA can print money to pay off its debt" nonsense in the Reinhart & Rogoff section.

Wonderful reality checksJ

Wonderful logical material with well presented examples. The only problem I have is that it was somewhat repetitive.