Statistical Methods with R

Working in RStudio

Unit A · Chapter 01 · Lecture 01b

Developed by Jeffrey M. Girard

Roadmap: Meeting R

R and RStudio
Console
Scripts
Activity

R and RStudio

Programming is a Superpower

Programming is how we talk to and control our amazing computers
It gives us power and flexibility
Everything we do in this course will be accomplished via programming
Programming will leave a record of what we did (i.e., code), so we can later reuse, adapt, and share it

Common Data Science Languages

General Purpose

R (interactive, welcoming)
- Strengths: statistics, data wrangling, data visualization
- Weaknesses: relatively slow, not security-focused

Python (popular, versatile)
- Strengths: automation, machine learning, data wrangling
- Weaknesses: relatively slow

Java / C++ / Scala / Julia (faster but older and harder or newer and smaller)

Special Purpose

JavaScript (web), SQL (databases), Swift (mobile), MATLAB (neuroscience), etc.

The R Ecosystem

Think of your computer as the engine of a car
- It provides raw power for computation

The R language is like the controls for the car
- It lets you apply and direct that power

RStudio is like a fancy dashboard for the car
- It adds extra information and convenience

An R package is like an add-on for the car
- It adds new features and capabilities

Installing R

Windows

Open a web browser
Visit cloud.r-project.org
Click “Download R for Windows”
Click the “base” subdirectory link
Click “Download R-4.X.X” (e.g., 4.5.1)
Run the downloaded .exe file
Select all the default options
Complete the installation wizard

Mac OS

Open a web browser
Visit cloud.r-project.org
Click “Download R for macOS”
Click “R-4.X.X.pkg” (e.g., 4.5.1)
Run the downloaded .pkg file
Select all the default options
Complete the installation wizard

Installing RStudio

Windows

Open a web browser
Visit rstudio.com/download
Scroll down until you find the table under the “All Installers” section
Find the row for “Windows 10/11”
Click “RStudio-2025.XX.X-XXX.exe”
Run the downloaded .exe file
Select all the default options
Complete the installation wizard

Mac OS

Open a web browser
Visit rstudio.com/download
Scroll down until you find the table under the “All Installers” section
Find the row for “macOS 13+”
Click “RStudio-2025.XX.X-XXX.dmg”
Run the downloaded .dmg file
Drag the RStudio icon to your Applications folder (if you want)

RStudio Window

Console

R will Grant your Wishes

R is like a well-meaning but overly literal genie
- It has the power to grant almost any wish
- But we must phrase our wishes carefully!
- We will always get what we ask for…
- …but not always what we wanted.

Mastering the R language means learning…
- How to properly phrase commands
- How to decipher error messages
- How to view code from R’s perspective
- How to detect and correct small mistakes

Communicating with R

The Console is like a chat window with R
- You send a command to R and get a response
- Neither side of the conversation is saved

An R Script is like an email thread with R
- You send many commands to R all at once
- Only your side of the conversation is saved

A Quarto Document is like a scrapbook with R
- You can combine code and formatted text
- Both sides of the conversation are saved

Console Live Coding

# Addition

10+3
10 + 3 # spaces are optional but recommended


# Subtraction

10 - 3


# Multiplication

10 * 3 # correct
10 x 3 # error


# Division

10 / 3 # correct
10 \ 3 # error


# Exponentiation

10 ^ 2


# Order of Operations

10 + 3 * 2
(10 + 3) * 2


# Negative Numbers

10 + -30


# Decimals and Fractions

1.234
(1 / 3)


# Leading and Trailing Zeros

09.870


# Large Numbers

9876543 # correct
9,876,543 # error
9 876 543 # error

Scripts

Script Live Coding

# Creating a new script

## Option 1: File > New File > R Script
## Option 2: Top bar: white square with green plus icon
## Option 3: Ctrl+Shift+N (Win) Cmd+Shift+N (Mac)
## A new pane will be added to the RStudio window called the Source Editor


# Entering commands into script

## In the Source Editor, we can add many lines of code to a script
## This allows for longer and more complex operations
## Think of it like drafting an email with many instructions
(1.4 + 2.8 + 9.3) / 3
30.1 - 24.7


# Running one line of code

## Hitting Enter (Win) or Return (Mac) does not run the code
## We can run one line of code at a time to see its results in console
## Option 1: With cursor on a line, click the Run button (top-right)
## Option 2: With cursor on a line, Ctrl+Enter (Win) or Cmd+Return (Mac)


# Running many lines of code

## We can run multiple lines of code at once to see results in console
## Option 1: Highlight lines with mouse, click the Run button (top-right)
## Option 2: Highlight lines with mouse, Ctrl+Enter (Win) or Cmd+Return (Mac)
## We can even run all lines of code in a script at once
## Option 1: Click the Source button (top-right)
## Option 2: Ctrl+Shift+Enter (Win) or Cmd+Shift+Return (Mac)


# Adding comments to scripts

## To help communicate the purpose of our code, we can add comments
## Comments will be ignored by R and are only there for human readers
## We always start a comment in an R script with a hash symbol: #
## I have been using comments in this very section you are reading!

# Calculate the average score on the quiz
(1.4 + 2.8 + 9.3) / 3

# Calculate the difference between exam 1 and exam 2
30.1 - 24.7

100 / 9 # we can even have comments at the end of line (start will still run)


# Saving the script file

## Option 1: File > Save
## Option 2: Source bar: blue and white disk icon
## Option 3: Ctrl+S (Win) Cmd+S (Mac)
## For now, save it wherever; we'll learn about Projects soon
## You will now have a .R file that you can keep and/or transfer
## Only the code/input is saved in the script, not the results/output