Practical Regression and Anova using R
by Julian J. Faraway
Number of pages: 213
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 more importantly, when they should be applied. Many examples are presented to clarify the use of the techniques and to demonstrate what conclusions can be made.
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by Norman Matloff - UC Davis
This book is for those who wish to write code in R, as opposed to those who use R mainly for a sequence of separate, discrete statistical operations. The reader's level of programming background may range from professional to novice.
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 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.
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.