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 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 Henk van Elst - arXiv
These lecture notes were written to provide an accessible though technically solid introduction to the logic of systematical analyses of statistical data to undergraduate and postgraduate students in the Social Sciences and Economics in particular.
by Sidney Tyrrell - BookBoon
This textbook is for people who want to know how to use SPSS for analyzing data. The author has considerable experience of teaching many such people and assumes they know the basics of statistics but nothing about SPSS, or as it is now known, PASW.
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.