Beginning R, Second Edition is a hands-on book showing how
to use the R language, write and save R scripts, read in data files, and write
custom statistical functions as well as use built in functions. This book shows
the use of R in specific cases such as one-way ANOVA analysis, linear and
logistic regression, data visualization, parallel processing, bootstrapping,
and more. It takes a hands-on, example-based approach incorporating best
practices with clear explanations of the statistics being done. It has been
completely re-written since the first edition to make use of the latest
packages and features in R version 3.

R is a powerful open-source language and programming
environment for statistics and has become the de facto standard for doing,
teaching, and learning computational statistics.  R is both an object-oriented language and a
functional language that is easy to learn, easy to use, and completely free. A
large community of dedicated R users and programmers provides an excellent
source of R code, functions, and data sets, with a constantly evolving
ecosystem of packages providing new functionality for data analysis. R has also
become popular in commercial use at companies such as Microsoft, Google, and
Oracle. Your investment in learning R is sure to pay off in the long term as R
continues to grow into the go to language for data analysis and research.

What You Will Learn:

• How to acquire and install R
  
• Hot to import and export data and scripts
  
• How to analyze data and generate graphics
  
• How to program in R to write custom functions
  
• Hot to use R for interactive statistical explorations
  
• How to conduct bootstrapping and other advanced
  techniques