Statistics with R
by Vincent Zoonekynd
Contents: Introduction to R; Programming in R; From Data to Graphics; Customizing graphics; Factorial methods; Clustering; Probability Distributions; Estimators and Statistical Tests; Regression; Other regressions; Regression Problems; Generalized Linear Models; Analysis of Variance; Mixed Models; Time series; Miscellaneous; Applications.
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by J H Maindonald - Australian National University
These notes are designed to allow individuals who have a basic grounding in statistical methodology to work through examples that demonstrate the use of R for a range of types of data manipulation, graphical presentation and statistical analysis.
by Roger D. Peng - Leanpub
This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies.
by Hadley Wickham
The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R's quirks...
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.