Think Bayes: Bayesian Statistics Made Simple
by Allen B. Downey
Publisher: Green Tea Press 2012
Number of pages: 77
Think Bayes is an introduction to Bayesian statistics using computational methods. Contents: Bayes's Theorem; Computational statistics; Tanks and Trains; Urns and Coins; Odds and addends; Hockey; The variability hypothesis; Hypothesis testing.
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by David Lane - Rice University
This is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.
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 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 Miguel A. Hernan, James M. Robins - Chapman & Hall/CRC
The book provides a cohesive presentation of concepts of, and methods for, causal inference. It will be of interest to anyone interested in causal inference, e.g., epidemiologists, statisticians, psychologists, economists, sociologists, and others.