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 Benjamin Yakir - The Hebrew University of Jerusalem
This is an introduction to statistics, with R, without calculus. The target audience for this book is college students who are required to learn statistics, students with little background in mathematics and often no motivation to learn more.
by R. Dennis Cook, Sanford Weisberg - Chapman & Hall
In this monograph, we present a detailed account of the residual based methods that we have found to be most useful, and brief summaries of other selected methods. Our emphasis is on graphical methods rather than on formal testing.
by Alex Reinhart - refsmmat.com
This is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. It assumes no prior knowledge of statistics, you can read it before your first statistics course.
by David W. Stockburger - Missouri State University
This e-book is a complete interactive study guide with quizzing functionality that reports to the instructor. The on-line text also has animated figures and graphs that bring the print graphic to life for deeper understanding.