Friday, July 17, 2020

Installation of "R" Software

Open source software R can be obtained from the R Project website. It does basic statistics, regression, and logistic regression. To obtain a free copy or to receive more information about R visit the R Project website:

www.r-project.org

Visit the main R web page (www.r-project.org); you see a Getting Started box with a link to download R. Click that link and you are directed to select a local CRAN mirror site from which to download R.

 

For Installing GNU R , download the installer for your operating system on CRAN. Launch the installer and follow the specific instructions for your operating system. Here are the addresses where you can find the installers for each OS:

• For Windows: http://cran.r-project.org/bin/windows/

• For Mac OS X: http://cran.r-project.org/bin/macosx/

• For Linux: http://cran.r-project.org/bin/linux/

 

Installation of Rstudio

RStudio-1.1.419

To download Rstudio , first visit www.rstudio.com and click on the "Download RStudio" button. From available options, select Open Source License RStudio Desktop by clicking on "Download icon for RStudio Desktop."

From “Installers for Supported Platforms”, Click on the version recommended for your system and save the file.  For Windows, Run the .exe file and follow the installation instructions.   

Use following command to install any packages in Rstudio.

Run R studio.  Console window in ‘R Studio’ will open.

Type following command / script and then press enter to install package.

install.packages('car', dependencies=TRUE, repos='http://cran.rstudio.com/')

 

Similarly, Install following packages.

install.packages('ggplot2', dependencies=TRUE, repos='http://cran.rstudio.com/')

install.packages('leaps', dependencies=TRUE, repos='http://cran.rstudio.com/')

install.packages('dplyr', dependencies=TRUE, repos='http://cran.rstudio.com/')

 install.packages('reshape2', dependencies=TRUE, repos='http://cran.rstudio.com/')

install.packages('Rcpp', dependencies=TRUE, repos='http://cran.rstudio.com/')

Book Resources for Analytics using 'R' software

  • Kabacoff, Robert I. (2015) R in Action, Data analysis and graphics with R, 2nd Edition, Manning publication.
  • Webster, Allen (2014). Introductory Regression Analysis with Computer Application for Business and Economics, Indian Edition, Routledge Publication.
  • Chatterjee, S. and Hadi, A. S. (2012). Regression Analysis by Example, 5th Edition, Wiley Student Edition.