Learning Statistics with R
by Daniel Navarro
Publisher: University of Adelaide 2014
Number of pages: 564
At its core, this is an introductory statistics textbook pitched primarily at psychology students. As such, it covers the standard topics that you'd expect of such a book: study design, descriptive statistics, the theory of hypothesis testing, t-tests, X2 tests, ANOVA and regression.
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by John Verzani - Chapman & Hall/CRC
A self-contained treatment of statistical topics and the intricacies of the R software. The book focuses on exploratory data analysis, includes chapters on simulation and linear models. It lays the foundation for further study and development using R.
by Joseph B. Kadane - Chapman and Hall/CRC
An accessible, comprehensive guide to the theory of Bayesian statistics, this book presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods.
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 David W. Stockburger - Missouri State University
The book for a course in multivariate statistics for first year graduate or advanced undergraduates. It is neither a mathematical treatise nor a cookbook. Instead of complicated mathematical proofs the author wrote about mathematical ideas.