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 Garrett Grolemund, Hadley Wickham - O'Reilly Media
This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science.
by Hadley Wickham - O'Reilly Media
This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham's package development philosophy. You'll work with devtools, roxygen, and testthat, a set of R packages.
by Julian J. Faraway
The emphasis of this text is on the practice of regression and analysis of variance. The objective is to learn what methods are available and when they should be applied. Many examples are presented to clarify the use of the techniques.
by Sivakumaran Raman - Smashwords
Learn R programming for data analysis in a single day. The book aims to teach data analysis using R within a day to anyone who already knows some programming in any other language. The book has sample code which can be downloaded as a zip file.