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 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.
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 Mohammed A. Shayib - Bookboon
The book introduces the concepts, definitions, and terminology of the subject in an elementary presentation with a mathematical background which does not surpass college algebra. It should prepare the reader to make a good decision based on data.
by Darius Singpurwalla - Bookboon
A Handbook for Statistics provides readers with an overview of common statistical methods used in a wide variety of disciplines. The book focuses on giving the intuition behind the methods as well as how to execute methods using Microsoft Excel.