NEW! Lessons
in Statistical Thinking by Daniel Kaplan. A complete
rethinking of a university-level introductory statistics course.
This is a replacement for the traditional introduction to statistical
inference. It emphasizes modeling, covariates, confounding, and causal
inference. It has a strong orientation to decision-making, treats
p-values repectfully by honestly as a curtailed form of Bayesian
inference. Lessons in Statistical Thinking was originally
envisioned as an extension for ModernDive:
Statistical Inference via Data Science , but has grown into a
text for a complete introductory or second statistics course.
A
Student’s Guide to R is organized by analysis method. It
demonstrates how to perform all of the statistical analyses typically
covered in an Intro Stats.