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ChatGPT Image Oct 21, 2025, 02_11_00 PM.png

Introduction to Data Analysis with R - Tuesdays 9am-12pm 3rd, 10th, 17th & 24th February 2026

£240.00

Taught across 4 Tuesday mornings in February 2026. Learn how to handle, analyse, and visualise data using R, one of the most powerful and widely used tools in data science and research. This hands-on, practical course is ideal for beginners—no prior experience with R is required.

Over four sessions, you’ll be guided step-by-step through key concepts in data analysis and statistical modelling. You’ll gain confidence writing R scripts, managing data, and applying statistical tests to real-world datasets.

Topics include:

  • Understanding R and RStudio: what is a script file?

  • Installing and using packages

  • Importing and cleaning data

  • Exploring data through summary statistics and plots

  • Introduction to linear models

  • Generalised Linear Models (GLMs) using count data

By the end of the course, you’ll have a clear understanding of how to use R for data analysis, interpret statistical results, and apply these techniques in your own work or research.

Taught across 4 Tuesday mornings in February 2026. Learn how to handle, analyse, and visualise data using R, one of the most powerful and widely used tools in data science and research. This hands-on, practical course is ideal for beginners—no prior experience with R is required.

Over four sessions, you’ll be guided step-by-step through key concepts in data analysis and statistical modelling. You’ll gain confidence writing R scripts, managing data, and applying statistical tests to real-world datasets.

Topics include:

  • Understanding R and RStudio: what is a script file?

  • Installing and using packages

  • Importing and cleaning data

  • Exploring data through summary statistics and plots

  • Introduction to linear models

  • Generalised Linear Models (GLMs) using count data

By the end of the course, you’ll have a clear understanding of how to use R for data analysis, interpret statistical results, and apply these techniques in your own work or research.

Introduction to Data Analysis with R Statistical Software

Day 1

09:00 – 09:30 Installation of additional software and accessing Dropbox materials

09:30 – 10:00 Introductions and welcome talk

10:00 – 12:00 Getting started with R and RStudio; syntax, scripts and data handling

12:00 – 13:00 Data wrangling 14:00 – 16:30 The General Linear Model –main effects and interactions, parameter estimates, contrasts and prediction graphs.

16:30 – 17:00 Practice with an example dataset

Day 2

10:00 – 10:30 Workshop session: Investigating your own data (formatting data and discussing research questions)

10:30 – 13:00 GLMs for count data

14:00 – 15:00 GLMs for binomial data

15:00 – 16:00 GLMs for Gamma data

16:00 – 16:30 Workshop session

16:30 – 17:00 End of course pep talk