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 C.E. Weatherburn - Cambridge University Press
This book provides the mathematical foundations of statistics. It explains the principles, and proves the formulae to give validity to the methods of the interpretation of statistical data. It is of interest to students of a wide variety of subjects.
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 David A. Kenny - Little, Brown
This textbook provides a first course in data analysis for students majoring in the social and behavioral sciences. The book is intended to be comprehensible to students who are not planning to go on to postgraduate study.
by David R. Lilja - University of Minnesota
The book presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models.