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 Thomas Hill, Paul Lewicki - StatSoft, Inc.
A comprehensive statistics textbook for both beginners and advanced analysts. It presents analytic approaches and statistical methods used in science, business, industry, and data mining, written for the real-life practitioner of these methods.
by A. M. Mood, F. A. Graybill, D. C. Boes - McGraw-Hill
A self contained introduction to classical statistical theory. The material is suitable for students who have successfully completed a single year's course in calculus with no prior knowledge of statistics or probability. Third revised edition.
by Keijo Ruohonen - Tampere University of Technology
Table of contents: Fundamental sampling distributions and data descriptions; One- and two-sample estimation; Tests of hypotheses; X2-tests; Maximum likelihood estimation; Multiple linear regression; Nonparametric statistics; Stochastic simulation.
by Jamie DeCoster - University of Alabama
It is important to know how to understand statistics so that we can make the proper judgments when a person presents us with an argument backed by data. Data are numbers with a context. We must always keep the meaning of our data in mind.