Bayesian Methods for Statistical Analysis
by Borek Puza
Publisher: ANU Press 2015
Number of pages: 697
A book on statistical methods for analysing a wide variety of data. Topics: bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code.
Home page url
Download or read it online for free here:
by Joseph B. Kadane - Chapman and Hall/CRC
An accessible, comprehensive guide to the theory of Bayesian statistics, this book presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods.
by D.M. Diez, C.D. Barr, M. Cetinkaya-Rundel - OpenIntro
OpenIntro Statistics is intended for introductory statistics courses at the high school through university levels. There are a large selection of exercises at the end of each chapter useful for practice or homework assignments.
by Robert B. Ash - University of Illinois
These notes are based on a course that the author gave at UIUC. No prior knowledge of statistics is assumed. A standard first course in probability is a prerequisite, but the first 8 lectures review results that are important in statistics.
by Denis Anthony - BookBoon
This is a practical book. It is aimed at people who need to understand statistics, but not develop it as a subject. The typical reader might be a postgraduate student in health, life, or social science who has no knowledge of statistics.