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.
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by Henry Lewis Rietz - Open Court Pub. Co
The book shifts the emphasis in the study of statistics in the direction of the consideration of the underlying theory involved in certain important methods of statistical analysis, and introduces mathematical statistics to a wider range of readers.
by Peter Young - arXiv
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results.
by Christian Akrong Hesse - ResearchGate GmbH
The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the applied sciences. Our goal is to introduce the basic theory without getting too involved in mathematical detail.
by David Brink - BookBoon
After reading the theory book about Statistics it is time to test your knowledge to make sure that you are well prepared for your exam. This free exercise book follows the same structure as the theory book about Statistics.