Install R & RStudio in 2026: The Setup That Actually Works First Time

To use Ryou install two things: R itself (the language engine) and RStudio (the editor you'll actually work in). R does the computing; RStudio makes it comfortable. Both are free and take about 5 minutes total.

Most installation guides show you where to click but skip the settings that save you hours later. This guide covers the full setup — installationverificationfirst-run settingsand the most common errors with their fixes — for WindowsMacand Linux.

Introduction

R is the programming language — the engine that runs your code. RStudio is an IDE (Integrated Development Environment) — the dashboard where you writerunand debug that code. You need bothand you must install R first because RStudio depends on it.

Think of it like this: R is the car engineRStudio is the cockpit with the steering wheeldashboardand GPS. You wouldn't drive an engine without a cockpit — and you wouldn't use R without RStudio.

Here's the plan:

1. Install R (the engine)
2. Install RStudio (the cockpit)
3. Verify everything works
4. Configure first-run settings
5. Install your first package

By the endyou'll have a fully working R development environment and will have run your first R code.

Prerequisites

Before installingmake sure your system meets these minimum requirements:

Already have R installed? If you have an older versionyou can install the new version alongside it. The installer won't break your existing setup. After installingRStudio will automatically use the newest version.

Step 1: Install R

R is distributed through CRAN (the Comprehensive R Archive Network). Here's how to install it on each operating system.

Windows

1. Go to the CRAN download page: https://cran.r-project.org/
2. Click "Download R for Windows"
3. Click "base" (this is the standard installation)
4. Click "Download R-4.x.x for Windows" (the version number will be the latest)
5. Run the downloaded .exe file
6. In the installer wizard:

• Accept the default installation directory (C:\Program Files\R\R-4.x.x)
• Accept the default components (all checked)
• Choose "No" when asked about customizing startup options (the defaults are fine)
• Click "Next" through the remaining screens and "Finish"

That's it. R is now installed. You'll see an "R" icon in your Start Menubut you won't use it directly — you'll use RStudio instead.

Mac

1. Go to https://cran.r-project.org/
2. Click "Download R for macOS"
3. Under "Latest release:"click the .pkg file that matches your Mac:

• Apple Silicon (M1/M2/M3/M4): Download the arm64 version
• Intel Mac: Download the x86_64 version
• Not sure which you have? Click the Apple menu → "About This Mac" → look for "Chip" (Apple M-series) or "Processor" (Intel)

1. Open the downloaded .pkg file
2. Follow the installation wizard — you'll need to enter your Mac password
3. Click "Install" and then "Close" when finished

Linux (Ubuntu/Debian)

Open a terminal and run these commands:

# Update package list
sudo apt update

# Install R
sudo apt install r-base r-base-dev -y

# Verify installation
R --version

For the latest R version (Ubuntu's default repos may be a version behind)add the official CRAN repository first:

# Add the CRAN GPG key
wget -qO- https://cloud.r-project.org/bin/linux/ubuntu/marutter_pubkey.asc | sudo tee /etc/apt/trusted.gpg.d/cran_ubuntu_key.asc

# Add the CRAN repository (replace "jammy" with your Ubuntu release codename)
sudo add-apt-repository "deb https://cloud.r-project.org/bin/linux/ubuntu $(lsb_release -cs)-cran40/"

# Update and install
sudo apt update
sudo apt install r-base r-base-dev -y

Step 2: Install RStudio

Now that R is installedinstall RStudio — the IDE you'll actually use every day.

Windows

1. Go to https://posit.co/download/rstudio-desktop/
2. The page auto-detects your OS. Click the big blue "Download RStudio" button
3. Run the downloaded .exe file
4. Accept all defaults in the installer — click "Next" through everything and "Finish"
5. Open RStudio from the Start Menu

Mac

1. Go to https://posit.co/download/rstudio-desktop/
2. Click "Download RStudio" — it'll download a .dmg file
3. Open the .dmg file
4. Drag the RStudio icon into the Applications folder
5. Open RStudio from the Applications folder or Launchpad

Mac security warning: If you get a "cannot be opened because the developer cannot be verified" messagego to System Preferences → Privacy & Security and click "Open Anyway" next to the RStudio message.

Linux (Ubuntu/Debian)

# Download the latest .deb package (check posit.co for the current URL)
wget https://download1.rstudio.org/electron/jammy/amd64/rstudio-2024.12.1-563-amd64.deb

# Install it
sudo dpkg -i rstudio-*.deb

# Fix any missing dependencies
sudo apt install -f -y

Then open RStudio from your application menu.

Step 3: Verify It Works

Open RStudio. You should see four panels:

1. Console (bottom-left) — where R code runs
2. Source (top-left) — where you write scripts (may be hidden until you open a file)
3. Environment (top-right) — shows your variables and data
4. Files/Plots/Help (bottom-right) — file browserplot viewerhelp docs

If you see these panelsRStudio found R automatically. Let's verify by running code.

Click in the Console panel (bottom-left)type the following lineand press Enter:

R.version.string

You should see something like: "R version 4.4.2 (2024-10-31)". If you see a version numberR is installed correctly.

Now try this longer test — you can run it right here in your browser to see what the output should look likethen compare it with what you get in your local RStudio:

If all five tests print output without errorsyour installation is perfect. Click Run above to see the expected outputthen try the same code in your local RStudio console.

Step 4: First Settings to Change

RStudio's default settings are mostly finebut there are three changes that will save you headaches later. Go to Tools → Global Options in RStudio:

4.1. Turn Off Workspace Saving

Go to General → Basic and change these:

• "Restore .RData into workspace at startup" → Uncheck this
• "Save workspace to .RData on exit" → Set to "Never"

Why? Old variables lingering from previous sessions cause hard-to-find bugs. You want every session to start clean. If you need data to persistsave it explicitly with saveRDS().

4.2. Set Your CRAN Mirror

Go to Packages and click "Change" next to the CRAN mirror. Choose a mirror close to your location:

• US: any US mirroror "0-Cloud" (which auto-selects the closest)
• Europe: your country's mirror
• Asia: Japan or Australia mirrors tend to be fast

This controls where R downloads packages from. A closer mirror means faster downloads.

4.3. Pick a Theme (Optional but Nice)

Go to Appearance and try different Editor themes. Popular choices:

• Tomorrow Night — dark themeeasy on the eyes
• Solarized Dark — warm tonespopular with developers
• Textmate — classic light theme

Also increase the font size if the default (10pt) feels small. Most people settle on 12-14pt.

Step 5: Install Your First Package

Packages extend R's capabilities. The tidyverse is the most important collection of packages for data science — let's install it to verify your package system works.

In RStudio's Consoletype:

install.packages("tidyverse")

This will take 1-3 minutes (it downloads and compiles several packages). You'll see lots of text scrolling — that's normal. When you see the > prompt againit's done.

Now verify it works. You can run this code in your local RStudio — or try it here first to see the expected output:

If you see a table with average MPG grouped by cylinder countyour package installation is working perfectly.

Now try creating a plot:

In your local RStudiothis plot will appear in the Plots panel (bottom-right). Click "Export" to save it as an image. Congratulations — you just created a publication-quality visualization.

Common Installation Errors (and How to Fix Them)

"R is not recognized as a command"

Problem: You installed R but the terminal can't find it.

Fix (Windows): Add R to your PATH. Search for "Environment Variables" in Windows Settingsedit the PATH variableand add C:\Program Files\R\R-4.x.x\bin. Or simply use RStudio — it finds R automatically.

Fix (Mac/Linux): Run which R in the terminal. If nothing showsR didn't install to the expected location. Reinstall using the steps above.

"RStudio: Unable to locate R"

Problem: RStudio can't find your R installation.

Fix: RStudio looks for R in standard locations. If you installed R to a custom pathtell RStudio where to find it: Tools → Global Options → General → R version → Change and browse to your R installation.

"Package installation failed: non-zero exit status"

Problem: A package failed to compile from source.

Fix (Windows): Install Rtools from https://cran.r-project.org/bin/windows/Rtools/. Rtools provides the compiler that some packages need.

Fix (Mac): Install Xcode Command Line Tools: open Terminal and run xcode-select --install.

Fix (Linux): Install development libraries: sudo apt install build-essential libcurl4-openssl-dev libssl-dev libxml2-dev.

"Warning: package was built under R version X.X.X"

Problem: A package was built for a different R version.

Fix: This is usually just a warningnot an error. The package will still work. To get rid of itupdate the package: install.packages("package_name").

"Cannot open connection" or "cannot open URL"

Problem: R can't reach the internet to download packages.

Fix: Check your internet connection. If you're behind a corporate firewall or VPNtry changing your CRAN mirror: options(repos = "https://cloud.r-project.org/") then retry the install.

Permission denied errors (Linux)

Problem: You can't install packages to the system library.

Fix: Don't use sudo for package installation. InsteadR will ask to create a personal library — say "yes". Packages will install to ~/R/ and work fine.

Alternative: Positron IDE

In 2025Posit (the company behind RStudio) released Positron — a new IDE built on VS Code's architecture. It supports both R and Python in one editor.

Should you use Positron instead of RStudio?

• If you're a beginner → stick with RStudio. It's more maturebetter documentedand all R tutorials assume you're using it.
• If you're experienced and already use VS Code → try Positron. It feels familiar and handles polyglot (R + Python) workflows well.
• If you just want to get started fast → RStudio is the safe choice.

We cover Positron vs RStudio in detail in a later tutorial. For nowRStudio is the recommended starting point.

Summary

Here's your complete setup checklist:

Total time: ~10 minutes. You're ready to start coding in R.

FAQ

Do I need to install R if I only want RStudio?

Yes. RStudio is just an editor — it doesn't include R itself. You must install R first (from CRAN)then install RStudio. RStudio will automatically detect and use your R installation.

Can I have multiple versions of R installed?

Yes. On Windows and Maceach R version installs to its own folder. In RStudiogo to Tools → Global Options → General → R version to switch between them. This is useful when a project requires a specific R version.

How do I update R to a new version?

Download and install the new version from CRAN — it installs alongside the old one. Then reinstall your packages. On Windowsthe installr package can automate this: installr::updateR().

Is RStudio really free?

Yes. RStudio Desktop (the open-source edition) is completely free and always will be. Posit (the company) makes money from RStudio Server ProPosit Connectand cloud services — not from the desktop IDE.

Can I use R without RStudio?

Yesbut you probably shouldn't. You can run R from the command lineor use other editors like VS Code (with the R extension) or Positron. But RStudio is purpose-built for R and provides the best experience for beginners: integrated helpvariable explorerplot viewerand package manager all in one window.

Continue Learning

Now that R and RStudio are installed and configuredyou're ready to start coding. The next tutorial walks you through the RStudio interface:

1. RStudio IDE Tour — learn what each panel does and the shortcuts that speed up your workflow
2. R Syntax 101 — write your first working R script
3. R Data Types — understand the building blocks of every R program

Each tutorial includes interactive code blocks — just like the ones on this page — so you can practice as you learn.