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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The goal of this handbook is to help scientists and engineers incorporate statistical methods in their work as efficiently as possible. Many parts of the book feature case studies or examples with computations from the free downloadable software.
by Michael Lavine
Upper undergraduate or graduate book in statistical thinking for students with a background in calculus and the ability to think abstractly. The focus is on ideas and concepts, as opposed to technical details of how to put those ideas into practice.
by Denis Anthony - BookBoon
This is a practical book. It is aimed at people who need to understand statistics, but not develop it as a subject. The typical reader might be a postgraduate student in health, life, or social science who has no knowledge of statistics.
by Ryan Martin - University of Illinois at Chicago
Table of contents: Statistics and Sampling Distributions; Point Estimation Basics; Likelihood and Maximum Likelihood Estimation; Sufficiency and Minimum Variance Estimation; Hypothesis Testing; Bayesian Statistic; What Else is There to Learn?