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

R is a powerful open-source language and programmingenvironment for statistics and has become the de facto standard for doing,teaching, and learning computational statistics.  R is both an object-oriented language and afunctional language that is easy to learn, easy to use, and completely free. Alarge community of dedicated R users and programmers provides an excellentsource of R code, functions, and data sets, with a constantly evolvingecosystem of packages providing new functionality for data analysis. R has alsobecome popular in commercial use at companies such as Microsoft, Google, andOracle. Your investment in learning R is sure to pay off in the long term as Rcontinues 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 advancedtechniques
  

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

R is a powerful open-source language and programmingenvironment for statistics and has become the de facto standard for doing,teaching, and learning computational statistics.  R is both an object-oriented language and afunctional language that is easy to learn, easy to use, and completely free. Alarge community of dedicated R users and programmers provides an excellentsource of R code, functions, and data sets, with a constantly evolvingecosystem of packages providing new functionality for data analysis. R has alsobecome popular in commercial use at companies such as Microsoft, Google, andOracle. Your investment in learning R is sure to pay off in the long term as Rcontinues 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 advancedtechniques
  

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

R is a powerful open-source language and programmingenvironment for statistics and has become the de facto standard for doing,teaching, and learning computational statistics.  R is both an object-oriented language and afunctional language that is easy to learn, easy to use, and completely free. Alarge community of dedicated R users and programmers provides an excellentsource of R code, functions, and data sets, with a constantly evolvingecosystem of packages providing new functionality for data analysis. R has alsobecome popular in commercial use at companies such as Microsoft, Google, andOracle. Your investment in learning R is sure to pay off in the long term as Rcontinues 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 advancedtechniques