[grayclhn]

I haven't looked at it carefully, but it's hard to think of a setting where I'd want to teach from this book: it's aimed at stats 101 students, but uses python as the programming language (great language, but far beyond what I'd expect a typical intro stats student to be able to handle); it advocates bayesian statistics, which is a reasonable decision, but seems to take it to such an extreme that "hypothesis test" never appears in the table of contents...

But, it's obviously a labor of love and it's an interesting take on intro to stats. And, from skimming it, I don't see anything in it that's wrong. So this might be a good intro to bayesian stats for most HN readers.

edit: there is a wide range of quality for the graphs, though. Some look great, but some (the histograms especially) are... unappealing. And the formatting for the code sections is quite at odds with the style of the rest of the book. Those are minor, though.

second edit: not to start a license flamewar, but can this book be redistributed? It's licensed under either CC or GNU FDL, but I don't see a way to get the source code. So anyone hosting a copy would also need to license it under the FDL (since they can't remove the FDL licensing from the pdf), which they would then be violating. Am I understanding things correctly, or am I wrong?

[sebastianavina]

The best book I've found about statistical inference is this one: http://www.amazon.com/exec/obidos/ASIN/188652923X/ref=nosim/... it comes with the bonus that you can take the full course (video lectures, recitations, assignments and quizes) on mit: http://ocw.mit.edu/courses/electrical-engineering-and-comput...

[findjashua]

thanks for the links. I've been meaning to kick the tires and read up on some probability/stats stuff, and this seems like the perfect way to ease back into it. Bookmarked!

[ced]

it advocates bayesian statistics, which is a reasonable decision, but seems to take it to such an extreme that "hypothesis test" never appears in the table of contents...

That's not very unusual. It seems to follow the "logic of science" approach from Jaynes. Hypothesis testing is covered in chapters 4 and 6. Other books (Mackay, Jaynes, Murphy) only cover frequentist hypothesis testing to argue against it, so this is rather refreshing.

[grayclhn]

It's very unusual to not cover hypothesis testing in an introduction to statistics class. The students are going to see "testing" again. The passage you quoted was about teaching from the book, not using it for self study.

[eli_gottlieb]

Whether the textbook author wants to preach the Way of Bayes or not, the students, provided they actually become empirical scientists, are going to face journal and conference reviewers who want to see p-values. Failing to teach them how to construct credible intervals and perform Bayesian significance testing based on posterior distributions is failing to teach them skills necessary for our profession.