Summary and Review: How to Lie With Statistics

Summary and Review: How to Lie With Statistics

An Honest-to-Goodness Bestseller

✍️ The Author

This book was written by Darrell Huff and published in 1954. Huff is well-known for publishing this best-seller and assisting the tobacco lobby as a statistician.

💡 Thesis of the Book

Statistics is a tool for trickster’s to fool the statistically ignorant. By learning how to swap fact for fiction using quantitative slight-of-hand, you’ll better prepared to catch the swindler’s red-handed.

“The secret language of statistics, so appealing in a fact-minded culture, is employed to sensationalize, inflate, confuse, and oversimplify.”

“This book is a sort of primer in ways to use statistics to deceive… Crooks already know these tricks. Honest men must learn them in self defense.”

💭 My Thoughts

This book is a data literacy classic that has influenced the way many of us interact with number-based claims, especially in the internet era. I know it certainly has given me a healthy dose of skepticism anytime I hear a statistically-backed claim or see a data visualization. In agreement with Tim Harford, I think this book is a bit too cynical. You walk away from it with the sense that statistics are a swindler’s tool, but it is much more than that. Andrejs Dunkels says it best, “It is easy to lie with statistics. It is hard to tell the truth without it.” I prefer Harford’s thesis in The Data Detective, which plants its flag in curiosity rather than cynicism. I do find the ironies surrounding this book rather amusing. After finishing the book, I glance at the backcover and had a good laugh. I saw the NY Times and the Atlantic stamp their approval on the backcover, which is like the captain of the titanic giving the foreword for a book about driving big boats. However, the real irony lies in what Huff did after writing this book. He was hired by the tobacco industry to manufacture doubt about the relationship between smoking and lung cancer through the use of “statisculation” (to borrow Huff’s term). In general, this book has a rich history and the principles one can derive from it are essential for navigating a digital landscape plagued with misleading information. I recommend it to everyone, regardless of statistical background, and in conjunction with Harford’s The Data Detective.

📕 Outline

The chapters are very brief, so I put together an outline for the entire book.