Bayesian Statistics Files

Bayesian Computation with R (bcwr) by Jim Albert
01 An Introduction to R
02 Introduction to Bayesian Thinking
03 Single-Parameter Models
04 Multiparameter Models
05 Introduction to Bayesian Computation
06 Markov Chain Monte Carlo Methods
07 Hierarchical Modeling
08 Model Comparison
09 Regression Models
10 Gibbs Sampling
11 Using R to Interface with WinBUGS

Statistical Rethinking: A Bayesian Course with Examples in R and Stan by Richard McElreath
00 Preface
01 The Golem of Prague
02 Small Worlds and Large Worlds
03 Sampling the Imaginary
04 Linear Models
05 Multivariate Linear Models
06 Overfitting, Regularization, and Information Criteria
07 Interactions
08 Markov Chain Monte Carlo
09 Big Entropy and the Generalized Linear Model
10 Counting and Classification
11 Monsters and Mixtures
12 Multilevel Models
13 Adventures in Covariance
14 Missing Data and Other Opportunities
15 Horoscopes