Statistics for Research Students

A full university statistics course written around the idea that the point of the method is the meaning you extract from the data. Covers sampling, estimation, hypothesis testing, and regression with real datasets at every step.

R. Nazim Khan

A rigorous treatment of the statistical methods used to analyze experimental measurements, covering error propagation, parameter estimation, likelihood, hypothesis tests, and deconvolution. Written for readers working with real experimental data.

Gerhard Bohm, Günter Zech

A very extensive treatment of modern statistical data analysis, covering regression, smoothing, causal inference, time series, and simulation, all worked through in R. Nearly 900 pages built from a Carnegie Mellon course.

Cosma Rohilla Shalizi