1  Lab: Introduction to R

Author

Gabriele Filomena

Published

October 5, 2026

The following material has been readapted from:

Open this lab in RStudio: in the Files pane, click labs and then 00.introR.qmd. Save your own copy in myLabs (File -> Save As...) and work on the copy. Work through it from top to bottom, running each code chunk. (First time? Follow the Setup guide first.)

This short lab shows you how to find your way around RStudio and how to run R code. It takes about 20 minutes. Then move on to Lab: Exploring a Dataset, the main practical for Week 1.

1.1 R and RStudio

R is a free program for statistics and data analysis. You use it by writing code, not by clicking menus. This takes a little getting used to, but it has a big advantage: your code is an exact record of every step of your analysis, so you (or anyone else) can run it again and get the same result.

RStudio is the program you use to write and run R code. In this module it runs in your browser, and R and all the packages you need are already installed.

1.1.1 The four panels

RStudio looks something like this:

  • Top left, Source: the file you are working on, for example this lab.
  • Bottom left, Console: where R runs code and prints the results. You can also type code here directly and press Enter. Ignore the Terminal tab next to it: you don’t need it.
  • Top right, Environment: the data and variables you have created so far.
  • Bottom right, Files / Plots / Packages / Help: your course folder, your charts, and help pages.

You can change the colours and font size in Tools -> Global Options -> Appearance.

1.2 Quarto documents and code chunks

The labs are Quarto documents (.qmd files). A Quarto document mixes normal text, like this paragraph, with code chunks: the grey boxes that contain R code. You will write your assessment report in the same kind of file.

A code chunk starts with ```{r} and ends with ```:

The buttons Source and Visual at the top left of the file switch between two views of the same file. In the Visual view you can also insert a chunk from Insert -> Executable Cell -> R:

To run a chunk, click the green arrow in its top-right corner. The result appears under the chunk.

Task: Run the chunk below.

print("hello world")
[1] "hello world"

Some useful shortcuts (use Cmd instead of Ctrl on a Mac):

Shortcut What it does
Ctrl+Enter Run the line where your cursor is
Ctrl+Shift+Enter Run the whole chunk
Ctrl+Alt+I Insert a new chunk (or use Code -> Insert Chunk)
Ctrl+S Save the file

To add your own notes, just type in the white space between chunks. To try out your own code, insert a new chunk.

1.3 R as a calculator

Task: Run each chunk in this section and check that you understand the result.

# Some simple addition. Text after a # is a comment: R ignores it.
2+3
[1] 5
6*8
[1] 48
4^3
[1] 64
exp(1)   # exp() is the exponential function
[1] 2.718282

R has most constants and mathematical functions you could want. For example, abs() gives the absolute value of a number, and round() rounds it to the nearest whole number.

pi     # the constant 3.14159265...
[1] 3.141593
abs(-1.77)
[1] 1.77
round(1.77)
[1] 2

1.3.1 Functions and arguments

abs() and round() are functions. The values you give a function inside the brackets are its arguments, separated by commas. Some arguments are required and some are optional.

The log() function calculates a logarithm. It takes the number x and the base. If you name the arguments, the order doesn’t matter:

log(x=5, base=10)
[1] 0.69897
log(base=10, x=5)
[1] 0.69897

If you don’t name them, R assumes that the first value is x and the second is base:

log(5, 10)
[1] 0.69897
log(10, 5)
[1] 1.430677

1.3.2 Getting help

To see what a function does and which arguments it takes, type ? followed by its name in the console, for example ?log. The help page opens in the Help tab, bottom right.

1.4 Variables

To use a result later, save it in a variable. R uses the arrow <- for this (= also works, but pick one and stick with it).

var <- 2*7.5       # create two variables
another_var <- 5   # notice they appear in the Environment panel
var
[1] 15
var * another_var
[1] 75

Variable names cannot start with a number or contain spaces, and they are case sensitive: var and Var are two different variables.

1.5 Packages

Packages add extra functions to R. For example, dplyr has functions for working with data and ggplot2 makes charts. All the packages you need in this module are already installed in your codespace. You just need to load a package with library() before you use it, once per session:

library(dplyr)   # load the dplyr package; we will use it in the next lab
Note

If you use RStudio on a university PC or your own laptop instead of the codespace, a package may be missing. You will see an error like there is no package called 'dplyr'. Install the package once with Tools -> Install Packages..., then run library() again. See Setup: RStudio on a PC or Laptop to install all the course packages at once.

1.6 Next

That’s all you need to start. Save this file (Ctrl+S), then open 01.DataExploration.qmd in the labs folder and save your copy in myLabs: Lab: Exploring a Dataset.