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.
Download or read it online for free here:
by Mohammad Saber Fallah Nezhad (ed.) - InTech
Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. The purpose of this volume is to provide some applications of Bayesian optimization and dynamic programming.
Statistics is used in almost every field of research. We will learn about subjects in modern statistics and some applications of statistics. We will also lay out some of the background mathematical concepts required to begin studying statistics.
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.
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.