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 Pete Kaslik
Contents: Statistical Reasoning; Obtaining Useful Evidence; Examining the Evidence Using Graphs and Statistics; Inferential Theory; Testing Hypotheses; Confidence Intervals and Sample Size; Analysis of Bivariate Quantitative Data; Chi Square; etc.
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 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.
by Brian S Blais - Save The Broccoli Publishing
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester.