Are there any good popular science book about statistics or machine learning?

Question

There a bunch of really good popular science books around, that deal with real science, as well as the history and reasons behind current theories, while remaining extremely enjoyable to read. For example, "Chaos" by James Gleick (chaos, fractals, nonlinearity), "A brief history of time" by Stephen Hawking (physics, origin of the universe, time, blackholes), or "The Selfish Gene" by Richard Dawkins (evolution and natural selection). Some of these books present arguments (Dawkins), and some don't (Gleick). But they all serve to make it easy for those of us without in-depth scientific educations to understand otherwise difficult concepts.

Are there any such books that focus mainly on Statistics, or machine learning?

Please include a summary of what each book covers.

Answer 1

I suspect The Lady Tasting Tea, by David Salsberg is exactly what you want. It's very much written in a narrative style, almost like a novel, with essentially no math (as I recall), so it would be accessible to anyone. I read it long ago and really enjoyed it. It reads very fast, and could give people a sense of what statistical analysis is about and how it can help us understand the world and solve practical problems.

Answer 2

Nate Silver's new book The Signal and the Noise: Why Most Predictions Fail – But Some Don't fits your description quite well. It is also an introduction into Bayesian thinking for laypeople. It got some attention lately and a review of the book can be found here.

Also worth checking out are Levitt & Dubner's Freakonomics books.

Answer 3

I would suggest the following books, though neither is ideal, you should check out:

1. The (Mis)Behaviour of Markets by (the great) B. Mandelbrot
2. Struck By Lightening by Jefferey Rosenthal

with the former more focused on finance, but still statsy, and the latter is a introduction to all the interesting probability subjects: odds, the Monty Hall problem, utility functions, random walks etc.

Answer 4

More good reads:

The Flaw of Averages by Sam L. Savage

Fooled By Randomness by Nassim Taleb

Both are somewhat cautionary books about being careful towards how to interpret probability and statistics in our everyday lives. For example, in financial markets, one might misuse an everyday gaussian distribution as a risk measure with disastrous consequences, and thus we might want to use more empirical based models (such as monte carlo simulations) in practice. Taleb is very popular in financial circles, and often cautions us to be more careful about behavioral biases and over-reliance on modelling

Answer 5

Ian Ayres is author of the book "Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart" which discusses several examples of data mining.

Answer 6

"The Theory That Would Not Die" by Sharon Bertsch McGrayne is a very readable book on the history of Bayesian statistics and the general idea behind it without getting too bogged down in the math.

I am also a fan of "The Cartoon Guide to Statistics" by Gonnick and Smith as a nice introduction to the general concept of statistics with some of the math, but presented in a way that does not put you to sleep (I also have the cartoon guides to genetics, physics, and chemistry and have read a couple of the others).

Answer 7

A very good book for aiding basic statistical literacy and statistical reasoning - and for making the case for these as important - is The Tiger That Isn't by Andrew Dilnot, the former presenter of a popular radio show about applied statistics for the BBC.

I often recommend it as the statistics equivalent of the popular pop science book Bad Science by Ben Goldacre. It's good for introducing basic statistical reasoning, for showing the importance of basic statistical reasoning, and getting people concerned about the lack of basic statistical reasoning among people who really should know better (particularly politicians, journalists, etc). Very accessible, engaging, funny in places, deeply worrying in others! Particularly good as an introduction for anyone who thinks of numbers as 'not their thing'.

Answer 8

The Drunkard's Walk by Leonard Mlodinow is an easy to read introduction to basic stats and probability. The content is aimed at an audience with no statistical or mathematical training, and there are no equations. I found it a little too dumbed down. There are lots of anecdotes relating various applications of bad statistics, and clear explanations of why they were wrong.

The book covers basic stats and conditional probability.