Welcome

This course is for people who feel a bit uneasy about learning R or statistics.

Maybe you’ve:

  • Opened R and had no idea what to do
  • Followed a tutorial and felt completely lost halfway through
  • Been told “it’s not that hard” and quietly disagreed
  • Enrolled in a class or course where this stuff is mandatory and are dreading what’s to come

That’s fine. You’re exactly who this is for. You don’t need to be “good at maths” or “a natural programmer” to learn this. You just need to be willing to try and to be a bit confused sometimes, but to keep going anyway.

How this course works

Most courses separate things that really shouldn’t be separate. You learn statistics, but not how to actually do or use them. Or you learn R code, but not what any of it means

Here, we do both, together.

Every lesson answers three questions:

  1. What does this mean?
  2. Why am I doing it?
  3. How do I do it in R?

We’ll go slowly, building intuition first, and only introduce complexity bit-by-bit.

One dataset, all the way through

We’ll use the Palmer Penguins dataset throughout the course. This includes real measurements of penguins, including:

  • Species
  • Body mass
  • Flipper length
  • Bill size

We’ll do it this was because constantly switching data makes learning harder. Sticking with one dataset lets you focus on understanding the underlying ideas and processes.

How to run the code

You’ll need somewhere to run R code. You’ve got two options:

Option 1: In your browser (easiest)

Use posit Cloud

  • No installation
  • Works immediately
  • Best if you just want to get started

Option 2: On your own computer

Install:

Then copy and run the code from each lesson.

If you plan on using R in the long term then a local installation is the way to go. If you’re unsure, however, posti Cloud allows you to avoid installation friction.

What you’ll learn

We’ll build knowledge and understanding step by step:

  1. Getting Started
    What R is, how to run code, and how to not feel lost immediately.

  2. Data & Penguins
    Understanding what data actually looks like in R.

  3. Visualisation
    Seeing patterns before trying to analyse them.

  4. Descriptive Statistics
    Summarising data: averages, variation, and distributions

  5. Are These Groups Different?
    Comparing groups using intuition first, then tools like t-tests.

  6. Working with Categories
    Understanding counts, proportions, and chi-square tests.

  7. When Data Gets Weird
    What to do when assumptions break (non-parametric alternatives).

  8. Relationships Between Variables
    Correlation and how variables move together.

  9. Linear Regression
    Building simple models and understanding what they mean.

How to use this course

  • Go in order (it’s designed that way)
  • Run the code yourself
  • Don’t worry if things don’t click immediately
  • Focus on understanding, not memorising

Now, move on to Module 1!

Next → Getting Started