Some are more focused in particular topic areas and maybe give a more authoritative treatment than this one. There are plenty of other great books out there covering much the same ground as this one. It appears the publisher's workflow suffered from a case of, spellcheck-checked!, but proofread?-meh, they must've had deadlines. Nevermind the unfortunate typos (at least in my printing). If the theses still have your interest, perhaps then read the chapters whole. These 'Don't be Fooled' sections give you the executive summary of the main ideas of the chapter, and include useful advice for use in your own analyses. If you've been sold on the book after this, the one-page summary notes at the end of each chapter are your next stop. If you're short on time and want the most value from this book, start by reading chapter nineteen, which provides an excellent summation of the books driving themes, in just eight pages. Levitt, Standard Deviations demystifies the science behind statistics and makes it easy to spot the fraud all around. 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.

With the breakout success of Nate Silver’s The Signal and the Noise, the once humdrum subject of statistics has never been hotter. Not only do others use data to fool us, we fool ourselves.

Today, data is so plentiful that researchers spend precious little time distinguishing between good, meaningful indicators and total rubbish. Other times, the well-intentioned are blissfully unaware of the mischief they are committing. Sometimes, the unscrupulous deliberately try to mislead us. 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.

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.Īs 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.

Book how to lie with statistics