Wrong Number: How to Extract Truth From a Blizzard of Quantitative Disinformation

by Aaron Brown

466 pages, Kindle Edition

Published April 28, 2026

Reviews

[Drew Ryan · Rating 4 out of 5]

I enjoyed reading this book. As a PhD engineer, I’m frequently frustrated by the poor quality of science that gets published, and the even lower quality that makes it into public discourse. Brown presents well considered analyses of a wide range of papers and reports, highlighting errors of different kinds. Throughout the book, he weaves in his personal experiences and thoughts what specifically is wrong in each analysis, and on how these problems could be avoided. Brown bounces between topics, which can be a little jarring, but overall provides a nice cross section of the problem, and did not detract from the overarching theme of the book. If you’re thinking about reading this book, it may be helpful to look at it as an anthology, rather than one long narrative, and it can easily be read in one-chapter chunks.

Brown is very open with his personal and political views, but he makes it very clear (in both word and deed) this isn’t an attack-book trying to target specific views he disagrees with. Wrong numbers and bad analyses are ubiquitous and trans-partisan.

There are a few editorial things that would have made the book more enjoyable for me personally. Early chapters describe math being done, but do not show equations. I think showing the equations would have been more helpful - later chapters included them, and even had little warnings advising readers that the equations could be skipped.

There were also some results that were presented in tabular form that would have made for good figures or charts, which can make the point a little snappier for the lay reader.

As a final note for the publisher, I read this as an ebook through Hoopla, and the table formatting gets messed up when the font size is changed from the default. I like to read on my phone with larger text, so this rendered some tables unreadable until I modified the text size for that page. A minor inconvenience, but it seems like one that could be fixed.

I’d recommend this book to anyone interested in the quality of science, the process of deriving new information, or to anyone that is just broadly intellectually curious. If you don’t like books that bounce between topics, this book probably isn’t for you.

[Drtaxsacto · Rating 5 out of 5]

Aaron Brown takes a dense subject and makes it fun. He covers the errors and misuses of statistics. The former is a problem but in our era of ideological science the latter is a greater problem. In the early 20th Century Francis Galton held a competition among experts and commoners on the weight of sheep at a fair. He found that the experts were no better at estimating those weights than the common people but he also found that if the collective judgements were summed the result would be very close to the actual weight.

The problem here is that in many cases experts only express their opinions with higher confidence.
Brown has a series of chapters on a diverse set of issues ranging from the effectiveness of disease prevention to managing betting odds in sports.

Hayek, in the Counter Revolution of Science, argued that by adding math into economics that the profession would become more obscure and possibly less accurate. Brown’s conclusion is to ask that all of us exercise prudence in responding to any statistic - especially if the creator says the “science is settled” - that is good advice.

[Dan · Rating 4 out of 5]

I’m glad I read this. It is an eye opener and gives you plenty of reasons to be skeptical about common wrong numbers and why they exist and who is behind some of them. I love math and while I made it through calculus, I never took a statistics class. I had a hard time following SOME of the math. This did not take anything away from the message or meaning for me.

[Murray Sondergard · Rating 3 out of 5]

This is an example of a book written without many numbers for a lay audience, that becomes incomprehensible because of the lack of numbers. Too many examples where the author asks the reader to take his word for it. Also, the book is a compilation of articles written elsewhere and then shoehorned into chapters in the book. As a result, there is little flow from one chapter to the next. Jarring changes in subject matter. I can't recommend this book.