How Not to Be Wrong

The Power of Mathematical Thinking

De: Jordan Ellenberg

Narrado por: Jordan Ellenberg

The Freakonomics of math—a math-world superstar unveils the hidden beauty and logic of the world and puts its power in our hands

The math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.

Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?

How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.

Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.

Great book

I found some of the mathematical equations difficult to follow by ear so it might be worth getting the digital version to follow along with, but I found the topic approachable and very interesting.

Reasoning

Lovely book on reasoning. I reccomend it to anyone interested in the study of critical thinking

I don’t write reviews

This book was ******* great! I really can’t explain how great it was. It’s worth your time.

Great story, but too many numbers for an audiobook

Very good narration! Very interesting to learn how apparently unconnected ideas are in fact connected. It would have been nice if the book had focused more on the concepts, ideas and story and had moved most of the supporting numerical data to an appendix.

Well worth it

Was this a book you wanted to listen to all in one sitting?

I looked forward to driving errands so I could listen to more of this book. The author has a knack for anecdotes that make just the right concrete point. The opening story, about fighter planes that come back with bullet holes in all the non-essential areas, was a perfect start to a cautionary section about selecting data bases and avoiding "survivor bias," which is as applicable to choosing high-performing mutual funds as it is to analyzing fighter plane vulnerabilities. He comes at each topic from a variety of angles, but has a firm enough grasp of his subject to tie them all together into the point he wants to make in each section.

Any additional comments?

I was sorry the author felt he had to reveal so much of his personal politics, but at least he chose aspects that illustrated what he wanted to say about reasonable and faulty styles of analyzing factual disputes. The whole book would have been worth it just for the discussion of how to spot shaky conclusions that depend on selecting a sample exclusively from data outliers, then inferring causation from the regression to the mean that ought to have been expected from the outset. (Thus some variety of the "_____ curse" that supposedly afflicts the performers with the best record in the first leg of a competition, when the rest of the season finds them performing at more their usual level.)