[edtechdev]

Here are some more interactive and effective ways to learn stats online. The Open Learning Initiative's open Probability & Statistics Course out of Carnegie Mellon might just be the most researched and carefully designed course out there. http://oli.cmu.edu/courses/free-open/statistics-course-detai... Students learn more statistics concepts in half the time as a traditional stats course. http://oli.cmu.edu/get-to-know-oli/see-our-proven-results/

The Statistics Online Computational Resource (SOCR) site is also amazing for actually learning and playing with common statistical tests and tools: http://www.socr.ucla.edu/

Collaborative Statistics is a free and interactive statistics textbook: https://www.kno.com/book/details/productId/txt9780983804905

You can also run Sage, R, Python, Octave (Matlab clone) and other tools right in the browser now: https://cloud.sagemath.com/

[tlmr]

What do you think of the CMU course vs this text book in question?

[capnrefsmmat]

The CMU course is very traditional. It covers basic exploratory data analysis (summary statistics, plotting data), basic probability, and hypothesis testing and estimation. There's no programming, nothing Bayesian, and only brief discussion of regression.

(I taught 36-201, the intro stats course that was used to build the OLI course, this summer.)

Statistical Inference, on the other hand, seems to take a Bayesian perspective and is very much not your standard intro stats class. It looks interesting and I'll have to skim through some of it.