Name: Teaching statistics
ISBN: 9780198572251

Teaching statistics

"Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class' - with exercises to break the ice and get students talking; then descriptive statistics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations and examples, how to encourage students to participate in class and to work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling."--BOOK JACKET.

What Hacker News says

chimeracoderMar 2013

I never thought I'd see a 31-page paper by Andrew Gelman on the front page of Hacker News. And certainly not a paper coauthored with a well-known frequentist!

I was lucky enough to work with Prof. Gelman as his research assistant while I was in school - I can't even being to tell you how prolific and brilliant that man is. His name may not be known very much outside academic circles, but I'd go as far as to say that he's the most important Bayesian statistician since Thomas Bayes.

He used to be a contributor to FiveThirtyEight, back before the Times picked it up. I used to explain FiveThirtyEight as 'one of the six blogs Andrew Gelman writes for'. Now, I explain Andrew Gelman as 'a former contributor to Nate Silver's blog'. How times have changed!

Gelman's approach to statistics is more wholly Bayesian than most people with a moderate level of statistical training are likely familiar with. It was from Gelman that I learned why I never need to perform an F-test[0]; at the same time, it was from Gelman that I learned some of the potential pitfalls of pure Bayesian reasoning[1] (and how to address them).

When people ask me where to get started with statistics, both of the books I recommend are Gelman's: Teaching Statistics: A Bag of Tricks and Data Analysis Using Regression and Multilevel/Hierarchical Models.

Both have tremendously off-putting titles, but they're actually incredibly accessible. Gelman is great at many things, but picking sexy titles is not one.

If you're interested in understanding the concepts behind this paper, I'd start there.

[0] http://andrewgelman.com/2009/05/18/noooooooooooooo/

[1] The linked paper provides a good analysis

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tom_bSep 2012

I would be interested in hearing specific recommendations for self-study of statistics from you.

I currently have Feller (based on reading www.ams.org/notices/200510/comm-fowler.pdf) but don't have a good "taste" for what would be the best books for a self-study approach to statistics. There is also the "Teaching Statistics: A Bag of Tricks" book and I was considering dropping it into the mix.

I am probably over-thinking the book choice and would be fine to just dive in to anything, but if I would prefer to not pick up references that are going to drive me off a good path to start . . .

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