R Installation Guide in Windows 11

This guide explains how to install R and RStudio on Windows 11 operating system.

Step 1: Standard Installation (via CRAN)

1.1: Install R (Core Language)

Go to: https://cran.rstudio.com/bin/windows/base/
Click Download R for Windows
Download and install R
Accept the default settings (recommended for beginners)

1.2: Install RStudio (IDE)

Go to: https://posit.co/download/rstudio-desktop/
Download RStudio Desktop for Windows
Install RStudio
Open RStudio — it will automatically detect R

You now have R and RStudio ready.

1.3: Launch and Verify

Open RStudio
In the Console, type:

version

If R prints its version information, the installation is successful.

Step 2: Create a New RStudio Project

Open RStudio
Click File → New Project → New Directory → New Project
Enter a project name (e.g., stats)
Choose a folder location
Click Create Project

Everything you do (scripts, data, plots) will stay inside this folder. This keeps your analysis organized and reproducible.

Step 3: Initialize a Project Environment with `renv`

Open the Console tab in RStudio
Install renv (only once):

install.packages("renv")

Initialize the project environment:

renv::init()

This creates a project-specific package library and a renv.lock file that tracks package versions.

Step 4: Install Required Packages

For general data analysis, install the following packages:

ggplot2 — plotting
dplyr — data manipulation
readr — reading CSV files

install.packages(c("ggplot2", "dplyr", "readr"))

These packages are installed only within this project environment.

Optional: If your analysis requires additional statistical measures (for example, Fisher / excess kurtosis), you may need to install extra packages such as e1071, only one package, so no c() needed. c() means, combine or concatenate.

install.packages("e1071")

The kurtosis() function in e1071 computes Fisher (excess) kurtosis, where a normal distribution has a value of 0. Pearson kurtosis is the original definition, where a normal distribution equals 3. Use Fisher/excess kurtosis for easier interpretation.

Step 5: Load Packages in Your Script

Click File → New File → R Script
Add the following at the top of your script:


library(ggplot2)
library(dplyr)
library(readr)

Save the script (File → Save or Ctrl+S / Cmd+S)
Click Source (top right of the script editor)
This runs the entire script from top to bottom, loading all packages at once

Step 6: Save Your Environment Snapshot

After installing packages and working on your analysis, type the following in the RStudio Console:

renv::snapshot()

This locks package versions. Anyone you share the project with can run:

renv::restore()

You now have a fully reproducible environment.