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 David Brink - BookBoon
This compendium of probability and statistics offers an instruction in the central areas of these subjects. The focus is overview. The book is intensively examplefied, which give the reader a recipe how to solve all the common types of exercises.
by David W. Stockburger - Missouri State University
This e-book is a complete interactive study guide with quizzing functionality that reports to the instructor. The on-line text also has animated figures and graphs that bring the print graphic to life for deeper understanding.
by Irving W. Burr - McGraw-Hill
The present book is the outgrowth of a course in statistics for engineers which has been given at Purdue University. The book is written primarily as a text book for junior, senior, and graduate students of engineering and physical science.
by Douglas S. Shafer, Zhiyi Zhang - lardbucket.org
This book is meant to be a textbook for a standard one-semester introductory statistics course for general education students. Our motivation for writing it is to provide a low-cost alternative to many existing popular textbooks on the market.