Have you been thinking about learning to analyse your data in R but are unsure where to start? This a gentle introduction to R for learners with no previous programming experience. It is not a classical programming course – we will not be talking about for-loops and variable types. These topics may become important to you later but you don't need them right at the start to get going. My goal is to give you the very basic toolkit you need to get you off the ground doing practical data analysis in R, as quickly as possible. Once you have those basics and are applying them to your own data, you will naturally pick up more advanced topics along the way.

 

This course is pre-recorded, meaning that you can work through the material when-ever and where-ever you feel like it. If you get stuck, you can ask for help in the discussion forum and I will help you out very soon.

Course curriculum

    1. Welcome!

    2. Just to get to know you a bit better...

    3. Why bother learning R?

    4. Why do YOU want to learn R?

    5. R vs RStudio

    6. Installing R

    7. Installing RStudio

    1. Opening up RStudio for the first time

    2. Using R as a fancy calculator

    3. Variables

    4. Practice creating variables

    5. Practice creating variables (solution)

    6. Quiz on variables

    7. Functions

    8. Vectors

    9. Practice vectors and functions

    10. Practice vectors and functions (solution)

    1. Download data

    2. Introduction to the data set

    3. Setting the working directory

    4. Reading in data

    5. The importance of the separator

    6. The importance of the separator (solution)

    7. Column and row names

    8. More fun with column names

    9. More fun with column names (solution)

    10. Indexing

    11. Practice row names and indexing

    12. Practice row names and indexing (solution)

    13. Conditional filtering

    14. Practice filtering

    15. Practice filtering (solution)

    16. Filter out observations with missing values

    17. Filter out observations with missing values (solution)

    1. Our first plot

    2. Customising your graphs

    3. Specify colours conditionally

    4. Specify colours conditionally (solution)

    5. Saving your graphs

    6. R documentation

    7. Make histograms

    8. Make histograms (solution)

    1. Calculating summary statistics

    2. Performing statistical tests

    3. Comparing groups

    4. Comparing groups (solution)

    1. Final thoughts

    2. Feedback

    3. BONUS: simple for loop

    4. BONUS: practice simple for loops

    5. BONUS: practice simple for loops (solution)

    6. BONUS: more interesting for loops

    7. BONUS: practice more interesting for loops

    8. BONUS: practice more interesting for loops (solution)

    9. BONUS: nested for loops

About this course

  • Free
  • 55 lessons
  • 1.5 hours of video content

Let's get learning!

Enroll today