Verify R is installed

After installation, open a terminal (macOS/Linux) or the R application (Windows) and type:

R.version.string

You should see something like "R version 4.4.x (2024-xx-xx)".

1. Go to https://posit.co/download/rstudio-desktop/
2. The page should auto-detect your OS. Click Download RStudio Desktop (the free version)
3. Run the installer and accept the defaults

RStudio divides its window into four panes. If you only see one or two, go to View → Panes → Show All Panes (Ctrl+Shift+0 on Windows/Linux, ⌘+Shift+0 on macOS).

<div class="tab active">Untitled1.R</div>
<div class="tab">analysis.Rmd</div>

<div class="pane-label"><span class="pane-num">1</span> Source</div>
<span style="color:#6a9955"># Write your scripts here</span><br>
x &lt;- c(2, 4, 6, 8)<br>
mean(x)

<div class="tab active">Environment</div>
<div class="tab">History</div>

<div class="pane-label"><span class="pane-num">2</span> Environment / History</div>
<span style="color:#9cdcfe">x</span>
<span style="color:#888">num [1:4] 2 4 6 8</span>

<div class="tab active">Console</div>
<div class="tab">Terminal</div>

<div class="pane-label"><span class="pane-num">3</span> Console</div>
<span style="color:#3fb950">&gt;</span> mean(x)<br>
[1] 5

<div class="tab active">Plots</div>
<div class="tab">Files</div>
<div class="tab">Packages</div>
<div class="tab">Help</div>

<div class="pane-label"><span class="pane-num">4</span> Files / Plots / Help</div>
<span style="color:#888">← your plots appear here</span>

A few settings will save you hours of debugging. Go to Tools → Global Options and make these changes:

General → Basic

• Restore .RData into workspace at startup → ☐ Unchecked
• Save workspace to .RData on exit → Never

Code → Editing

• Use native pipe operator |> (requires R ≥ 4.1) → ☑ Checked (optional but modern)
• Auto-indent code after paste → ☑ Checked
• Insert matching parens/quotes → ☑ Checked

Appearance

Choose a theme and font size that you are comfortable reading for hours. Popular choices:

• Themes: Cobalt, Dracula, Monokai (dark); Chrome (light)
• Editor font: Source Code Pro or Fira Code
• Font size: 13–14pt for most screens

Click Apply → OK when done.

RStudio Projects keep your scripts, data, and outputs together and set the working directory to the project folder automatically — no more setwd("/Users/my/deeply/nested/path").

1. Go to File → New Project
2. Choose New Directory → New Project
3. Name it something like EA030 and choose where to save it
4. Click Create Project

You will see a .Rproj file appear in the Files pane. Double-clicking it from Finder/Explorer reopens the project with all your files.

Create a new script

Go to File → New File → R Script (or press Ctrl/⌘+Shift+N). A blank Source pane opens. Save it immediately as setup_test.R with Ctrl/⌘+S.

Run the code below

Type (or paste) the following into your script. Select all with Ctrl/⌘+A, then run with Ctrl/⌘+Enter:

# ── Basic arithmetic ──────────────────────────────────────────────
x <- c(2, 4, 6, 8, 10)         # create a numeric vector
mean(x)                          # mean

## [1] 6

sd(x)                            # standard deviation

## [1] 3.162278

summary(x)                       # five-number summary

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##       2       4       6       6       8      10

# ── A simple plot ─────────────────────────────────────────────────
plot(x, x^2,
     main = "Test Plot — x versus x²",
     xlab = "x",
     ylab = expression(x^2),
     col  = "#4a7c5e",
     pch  = 16,
     cex  = 1.5)
abline(lm(x^2 ~ x), col = "#c8832a", lwd = 2, lty = 2)

The plot should appear in the Plots pane (pane 4). Use the left/right arrows at the top of the Plots pane to navigate plot history.

Running code: three ways

R Markdown (.Rmd) files weave together prose, code, and output into a single reproducible report. Every tutorial in this course is an Rmd file — including this one.

Create your first Rmd

1. Go to File → New File → R Markdown…
2. Fill in the dialog:
   • Title: My First Report
   • Author: your name
   • Output Format: HTML (default)
3. Click OK

RStudio opens a template with a YAML header and some example chunks. The top of the file looks like this:

---
title: "My First Report"
author: "Your Name"
date: "`r Sys.Date()`"
output: html_document
---

Key Rmd elements

Add your own chunk

Click where you want a chunk, then use Insert → R or press Ctrl/⌘+Alt+I:

```{r stream-plot}
# Dissolved oxygen versus temperature
temp <- seq(10, 25, by = 1)
DO   <- 14.6 - 0.38 * temp
plot(temp, DO,
     type = "l", lwd = 2, col = "#4a7c5e",
     xlab = "Temperature (°C)", ylab = "DO (mg/L)",
     main = "DO–Temperature Relationship")
```

Click the Knit button (the blue yarn-ball icon) at the top of the Source pane, or press Ctrl/⌘+Shift+K.

RStudio will:

1. Start a fresh R session (separate from your current one)
2. Run every code chunk from top to bottom
3. Weave the output together with your prose
4. Write an .html file to the same folder as your .Rmd
5. Open a preview in the Viewer pane

Useful chunk options

Chunk options go inside the {r} header and control how output appears:

```{r my-plot, echo=FALSE, fig.cap="My caption", fig.height=4}`r ''`
# echo=FALSE  — run code but hide the source in the output
# fig.cap     — add a caption below the figure
# fig.height  — set figure height in inches (fig.width also available)
# eval=FALSE  — show code but don't run it
# include=FALSE — run code silently, hide everything

---

<div class="step-header">
<div class="step-num">9</div>
<div>
<div class="step-title">Install Packages</div>
<div class="step-sub">Extend R with community-built tools</div>
</div>
</div>

Base R covers arithmetic, basic statistics, and simple plots. For environmental data science you will need additional packages. Install them once from CRAN:


``` r
# Core packages used throughout EA030
# Run once — you do NOT need to reinstall each session
install.packages(c(
  "tidyverse",    # ggplot2, dplyr, tidyr, readr, and more
  "lme4",         # mixed-effects models
  "lmerTest",     # p-values for lme4
  "car",          # added-variable plots, Anova()
  "MuMIn",        # model selection (AIC, R²)
  "vegan",        # multivariate ecology
  "sf",           # spatial data
  "lubridate",    # dates and times
  "janitor",      # data cleaning utilities
  "here"          # robust relative paths
))

Update packages

Keep packages current with:

update.packages(ask = FALSE)   # update all installed packages

What’s next?

• Module 01 — Project Structure & File Organisation — reproducible folder layouts, relative paths with here, and naming conventions
• Module 02 — R Markdown & knitr in Depth — YAML options, chunk options, tables, and cross-references
• Module 03 — Data Import — reading CSV, Excel, and field-data files with readr and janitor