Book about statistics lighter than academic ones Christmas is coming and I would like to make a statistics-themed gift. The recipient bought and liked How Not to Be Wrong by Jordan Ellenberg (btw, I like that book too). He also liked The Signal and the Noise, even though he found it a bit light on math. Thus I'm looking for something like these books, i.e. statistics-themed, not afraid of a few equations but lighter than a big caliber academic book such as for example BDA by Gelman et al. Can you suggest me a few titles?
EDIT: I just found out that he owns also Risk Savvy: How to Make Good Decisions by Gigerenzer but not Kahneman's book, so the suggestion by Glen_b seems spot on.
 A: Dicing with Death by Stephen Senn focuses on medical statistics and is a lot more mathematical than The Signal and the Noise. I liked it but it does contain quite a lot of typos.
The Lady Tasting Tea covers a lot more ground than I expected and is one of the most open-minded statistics books that I have read. Although it is not at all mathematical, it does introduce a lot of interesting topics.
Symbols, Signals and Noise by Pierce is very cheap, easy to read and contains a lot of equations. It sounds like a great fit but is quite old (it's published as a Dover reprint.)
If your friend is interested in history, Games, Gods and Gambling by Florence Nightingale David is an account of the early history of statistics that is very heavy on the mathematics. I much prefer her writing to Stigler, but it's not really pop-sci, so maybe not suitable for your friend.
A: On the lighter side of things?
Statistics Done Wrong: The Woefully Complete Guide Is a fun title on, well, the title is self explanatory.
In the same vain, a classic is How to Lie With Statistics. Similar-ish but with a slight Freakonomics vibe is Naked Statistics: Stripping the Dread from the Data
A: Not at all mathematical, but certainly has some statistical elements:
Kahneman, D. (2011) Thinking, Fast and Slow
It's 5 years old so the person might just have read it but if they have not they might find it valuable.
A: THE ACCIDENTAL STATISTICIAN an autobiography of G.E.P Box makes great (light) reading. It is not as heavy as the Ellenburg book which I just loved but enjoyable none the less as it describes the paths taken by all when trying to make sense out of numbers.
A: The History of Statistics: The Measurement of Uncertainty before 1900 by Stephen M. Stigler
I never read it back-to-back, just used it few times as a reference, but it's a nice book that could be interesting for a wide variety of readers.
A: For a physics flavor, Anomaly!, by Tommaso Dorigo is about the "discovery" of anomalous signals at several particle physics colliers in the 1990s, and the study of whether these were discoveries of new physics or statistical/methodological flukes. It is a bit pricey, however.
A: Sharon Bertsch McGrayne, The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy

Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.
In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.
Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

