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 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.
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 Michael Falk at al. - University of Wuerzburg
This book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. The book addresses students of statistics, economics, demography, engineering.
by Hugh D. Young - McGraw Hill
A concise, highly readable introduction to statistical methods. Even with a limited mathematics background, readers can understand what statistical methods are and how they may be used to obtain the best possible results from experimental data.