Introduction to R and RStudio

Data Skills for Psychology — Module 1

Welcome!

These slides are adapted from Applied Data Skills Ch. 1.

Today’s Goals

By the end of this class, you will be able to:

Install R and RStudio
Install add-on packages
Get help for packages and functions
Create objects by writing and running code in the console

What is R?

R is a programming language designed for statistics and data analysis.

Think of R as the engine of a car — it does all the work under the hood.

Why R?

Free and open-source
Thousands of add-on packages
Massive community (especially in psychology!)
Makes your work reproducible

What is RStudio?

RStudio is an Integrated Development Environment (IDE) — it makes working with R much easier.

If R is the engine, RStudio is the dashboard, steering wheel, and GPS all in one.

Warning

Always launch RStudio, not R directly!

🛠️ Setup Check

Activity: Installation Check

Do this now!

Open RStudio on your computer
Check: do you see four panes?
Give a thumbs up when you’re ready!

If you haven’t installed R and RStudio yet, follow the installation guide.

The RStudio IDE

The Four Panes

Upper Left: Source

Write and edit code
View data tables

Lower Left: Console

Type commands directly
See output

Upper Right: Environment

See your objects
View your data

Lower Right: Files/Plots/Help

File browser
Plot viewer
Help documentation
Package manager

Activity: Explore the Panes

Try it!

Find the Console pane — type 1 + 1 and press Enter
Find the Environment pane — is it empty?
Find the Help pane — type ?mean in the console
Where did the help appear?

Note

You can rearrange panes under Tools > Global Options > Pane Layout

⚙️ RStudio Settings

Critical Settings to Change

You should always start with a clean workspace — no leftover objects from last time!

Do this now!

Go to Tools > Global Options > General:

Uncheck “Restore .RData into workspace at start-up”
Set “Save workspace to .RData on exit” to Never

Warning

You’ll need to change these settings every time you update RStudio.

📦 Packages

What are Packages?

R comes with built-in functions (“base R”) — like the default apps on your phone.

Packages are add-ons created by the R community — like apps you download from the App Store.

There are thousands of packages for:

Data visualization 📊
Machine learning 🤖
Web scraping 🌐
Interactive dashboards 📱
Even playing Sudoku! 🧩

Install vs. Load: A Key Distinction

`install.packages()`

📲 Like downloading an app

Do it once
Only from the console
Stays until you remove it

`library()`

🚀 Like launching an app

Do it every session
Put it in your script
Only lasts until you close R

Activity: Install Your First Packages

Run these in the console (not a script!)

install.packages("tidyverse")
install.packages("beepr")

Important!

Never put install.packages() inside a script — only run it from the console. Why? You might accidentally reinstall and update a package, which could break your code.

Activity: Load and Use a Package

Try it!

# Load the package
library(beepr)

# Use a function from the package
beep()

🔊 Make sure your sound is on! What did you hear?

Now try this:

beep(sound = 8)

What changed? Try values 1 through 11!

Functions

Anatomy of a Function

A function is a named piece of reusable code. It takes arguments (inputs) and produces output.

function_name(argument1 = value1, argument2 = value2)

For example:

beep(sound = 8)
#     ^         ^
#     |         |
#  argument   value

The Tidyverse

tidyverse is a “meta-package” — a bundle of packages we’ll use throughout this course:

Package	Purpose
`ggplot2`	Data visualization
`dplyr`	Data manipulation
`tidyr`	Data tidying
`readr`	Reading data files
`stringr`	Working with text
`forcats`	Working with categories
`lubridate`	Working with dates

Getting Help

There are several ways to get help with a function:

# If the package is loaded
?beep

# If you're not sure about the package
??beep

# The full specification
?beepr::beep

Every help page has the same structure: Description → Usage → Arguments → Details → Examples

Tab Auto-Complete

One of RStudio’s best features! Start typing a function name and press Tab:

RStudio will show you matching functions
Select a function and press Tab again to see its arguments
Each argument comes with a brief description

Try it!

Type sam in the console and press Tab. Select sample( and press Tab again to see the arguments.

Arguments In Practice

Example: `sample()`

# Randomly pick 5 letters
sample(x = letters, size = 5)

[1] "d" "q" "n" "v" "y"

# Allow duplicates
sample(x = letters, size = 5, replace = TRUE)

[1] "m" "c" "b" "i" "e"

Named vs. Positional Arguments

These two lines do the same thing:

# Named arguments (explicit)
sample(x = letters, size = 5, replace = TRUE)

# Positional arguments (implicit)
sample(letters, 5, TRUE)

With named arguments, order doesn’t matter:

sample(size = 5, replace = TRUE, x = letters)

Note

When learning, use named arguments — they make your code easier to read!

Objects

Creating Objects

Objects store things — numbers, text, dates, results. Use <- to assign values:

name <- "Maureen"
age <- 42
today <- Sys.Date()
halloween <- as.Date("2026-10-31")

To see what’s inside an object, type its name:

name

[1] "Maureen"

today

[1] "2026-06-01"

Types of Data

Object	Type	Key Rule
`name <- "Maureen"`	Character (text)	Must use quotes `" "`
`age <- 42`	Numeric (number)	No quotes
`today <- Sys.Date()`	Date (dynamic)	Changes each day!
`halloween <- as.Date("2026-10-31")`	Date (fixed)	Wrapped in `as.Date()`

Check the Environment pane — your objects should appear there!

Objects Can Interact

name <- "Maureen"
age <- 42
today <- Sys.Date()
halloween <- as.Date("2026-10-31")

decade <- age + 10
full_name <- paste(name, "Ritchey")
how_long <- halloween - today

decade

[1] 52

full_name

[1] "Maureen Ritchey"

how_long

Time difference of 152 days

Activity: Create Your Own Objects

Type this into your console

Create objects for your name, age, and a date you’re looking forward to
Calculate how many days until that date
Use paste() to create a sentence like: “Hi [name] — there are [X] days until [event]!”

# Example structure
name <- "Your Name"
today <- Sys.Date()
my_date <- as.Date("2026-12-25")
days_left <- my_date - today
message <- paste("Hi", name, "— there are",
                 days_left, "days to go!")
message

Getting Help

Your Help Toolkit

Resource	When to Use
`?function_name`	Know the function, need details
`??search_term`	Not sure which function to use
Google + “R” or “tidyverse”	Stuck on a concept
AI tools (responsibly!)	Need examples or explanations
Package vignettes	Want a tutorial-style guide
Your classmates!	Always a good idea

A Note on AI

AI tools can help with coding — but be careful while you’re building foundational skills.

Using AI to do your exercises is like getting a forklift to lift weights at the gym for you. It defeats the purpose!

Build your skills first, then use AI to accelerate your work — not replace your learning.

Wrapping Up

Key Takeaways

R is the language; RStudio is the tool that makes it easier
Always start with a clean workspace
install.packages() = download once; library() = load each session
Functions take arguments; use ? to learn about them
Objects store your data; use <- to create them
When stuck: restart R, check help, Google it, ask a friend!

Before Next Time

📖 Read: Chapter 1 of Applied Data Skills to lock in what we learned today

❓ Questions?

Introduction to R and RStudio

Welcome!

Today’s Goals

What is R?

What is RStudio?

🛠️ Setup Check

Activity: Installation Check

The RStudio IDE

The Four Panes

Activity: Explore the Panes

⚙️ RStudio Settings

Critical Settings to Change

📦 Packages

What are Packages?

Install vs. Load: A Key Distinction

install.packages()

library()

Activity: Install Your First Packages

Activity: Load and Use a Package

Functions

Anatomy of a Function

The Tidyverse

Getting Help

Tab Auto-Complete

Arguments In Practice

Example: sample()

Named vs. Positional Arguments

Objects

Creating Objects

Types of Data

Objects Can Interact

Activity: Create Your Own Objects

Getting Help

Your Help Toolkit

A Note on AI

Wrapping Up

Key Takeaways

Before Next Time

`install.packages()`

`library()`

Example: `sample()`