Are you new to statistics or looking for a solid refresher? This four-day introductory course provides a practical foundation in statistical thinking and data analysis. The programming language R is used throughout the course as a practical tool to perform the analyses, visualise the data, and interpret the results.
Designed for beginners, the course combines essential statistical concepts with hands-on exercises. You will learn how to explore data, choose appropriate statistical methods, perform analyses in R, and correctly interpret the results. Theory is immediately reinforced through practical examples, allowing you to apply each concept to realistic datasets.
By the end of the course, you will have a solid understanding of the statistical techniques most commonly used in research and professional practice, and you will be able to confidently apply them to your own data.
More information:
Course contents
Part 1: Underlying concepts of statistics
- Types of variables
- Descriptive statistics
- Normal distribution
- Parameter estimation
Part 2: Hypothesis testing
- Principles of a hypothesis test
- Type 1 and Type 2 error
- Power analysis and sample size calculation
- Parametric and non-parametric testing
- t-test, anova and non-parametric alternatives
- Chi-square test
- Simple linear regression
Target audience / prerequisites
Pre-and postdoctoral students from all fields of research.
No previous experience with statistical techniques is required.
Basic understanding of programming in R is useful, but not required.
Instructors
Dr. Annelies Agten
Time and Place
This 4-day course will take place on October 5-6-7-8, 2026 at Stadscampus (room TBD)
The course will start at 9.30 and will finish at the latest at 15.00 each day (with a one hour lunch break around 12.00).
Price
| PhD student ADS | € 100 |
| UA-affiliated | € 180 |
| Academic non-UA | € 320 |
| Nonprofit/public sector | € 500 |
| Private sector | € 1000 |