Teaching Statistics

Doing this is now, officially, what I am paid for. I am basically unembarrassed about doing this while never having taken a statistics class --- after all, I do statistical research, so it's not exactly like a celibate man offering advice on marriage --- but I do want to do it better.

One thing which particularly concerns me is that almost all the introductory textbooks I run across seem like either cookbooks, or lower and distorted forms of Cramér's Mathematical Methods of Statistics. Cramér's book is great, but giving a debased version of it to engineers or social scientists doesn't seem all that effective. So I'm interested in good approaches to teaching statistics as a way of learning about the world from data, not a set of rituals or a calculational exercise in basic probability theory. If they do a good job of teaching about computer-intensive methods and applied probability, so much the better.

In fact, what I'd really like is for somebody to write a popular book on "better living through data analysis". I wish I could say that Freakonomics was that book, but it isn't.

Larry Gonick and Woollcott Smith, The Cartoon Guide to Statistics
D. Huff, How to Lie with Statistics
Larry Wasserman, All of Statistics

Robert P. Abelson, Statistics as Principled Argument ["Author's note: There is a Robert P. Abelson who sings in the Yiddish theater in New York. Although theatrically inclined, I cannot (alas) claim to be that person also."]
Richard A. Berk, Regression Analysis: A Constructive Critique [My comments]

Nathan Moore, Nicole Schoolmeesters, "Computational Physics and Reality: Looking for Some Overlap at the Blacksmith Shop", arxiv:0904.3960 [This sounds like it might also work for a course in stochastics...]

Murray Aitkin, Brian Francis, John Hinde and Ross Darnell, Statistical Modelling in R [Blurb]
Benjamin M. Bolker, Ecological Models and Data in R [blurb, intro]
F. M. Dekking, C. Kraaikamp, H. P. Lopuhaä and L. E. Meester, A Modern Introduction to Probability and Statistics: Understanding How and Why [Blurb]
Finkelstein, Smith and Levin, Statistics for Lawyers ["Despite its pedestrian title, it is not a routine statistics text with legal examples tossed in. The selection of topics and examples, as well as the exposition of statistics and law, is erudite, informed, and even entertaining." --- or so says the review quoted by Springer Verlag]
Andrew Gelman and and Deborah Nolan, Teaching Statistics: A Bag of Tricks
Phillip I. Good, Resampling Methods: A Practical Guide to Data Analysis
Phillip I. Good and James W. Hardin, Common Errors in Statistics (and How to Avoid Them)
Dana K. Keller, The Tao of Statistics: A Path to Understanding (With No Math)
Gary King, Robert O. Keohane and Sidney Verba, Designing Social Inquiry: Scientific Inference in Qualitative Research [Blurb, preface, ch. 1]
Ben Klemens, Modeling with Data [website with draft text. Looks interesting and I like the idea of integrating it with computing, and with databases. (But I've forogtten almost everything I knew about databases.)]
Neil J. Salking, Statistics for People Who (Think They) Hate Statistics
Aris Spanos, Probability Theory and Statistical Inference
Jefferson Hane Weaver, Conquering Statistics: Numbers Without the Crunch

Notebooks

Teaching Statistics