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