This is a variant on the Data Science Curriculum for
Engineers which includes Peter Dalgaard's book for self-study. Only the
statistics section is shown in this document; refer to the primary document
for all other sections.
OpenIntro Statistics and Introductory Statistics with R
Recommended Chapter Sequence
Basic intro, about ½ of which is redundant with R4DS. Quick and easy.
Probability. Nontrivial if this is your first time seeing it. Easy if you did it before.
Distributions; very important. The most important distributions are the normal and binomial;
do not memorize the others.
How to use those distributions in R. Short but very important.
Confidence intervals and the central limit theorem. Important.
Statistical tests for continuous data and power tests. Very important.
How to do t tests in R. Very important; nobody does these by hand.
How to do power tests in R; also important.
ANOVA in R. Advanced; optional.
Statistical tests for proportions (e.g. clicks) is very important. X2
also useful; not critical.
Proportion tests in R; important.
We do not use chapters 7 and 8 in OpenIntro Statistics