# Chapter 4 Setup

The next set of technical chapters are intended to give you more hands-on guidance for using R in an audit environment. You should have R and RStudio installed, as well as some of the packages we intend to use.

There are countless number of guides to setting up your local R and RStudio environment. If you’re learning on your own, its easy to get some of the below applications and packages installed.

## 4.1 R with RStudio

One of the most respected introductions to R is R for Data Science by Hadley Wickham and Garrett Grolemund, and the Prerequisities section is set up for installing R.

## 4.2 Common packages

We will use several common packages; if you haven’t installed them yet, feel free to install them into R:

install.packages(c('tidyverse', 'lubridate', 'readr',
'DBI', 'devtools',
'gt', 'pryr', 'stringi',
'rmarkdown',
'tidymodels', 'tidytext', 'tm', 'rpart', 'rpart.plot',
'jsonlite', 'httr'))

## 4.3 Highbond R package

For those customers who use the cloud-based Galvanize Highbond (and specifically the Results Module), we will use the R package galvanizer to use Results information in the Applied Analytics chapter. This package is maintained by Jonathan Lin during his spare time, and any issues or suggestions on its improvement would be appreciated.

install.packages('galvanizer')