| Title | Time | Room | Teacher |
|---|---|---|---|
| Introduction to Statistics in R | 06.06.2025 09:30 - 16:30 (Fri) | online | Dr. Nicolas Attalides |
| Introduction to Statistics in R | 13.06.2025 09:30 - 16:30 (Fri) | online | Dr. Nicolas Attalides |
This course provides a hands-on introduction to statistical analysis in R, covering essential concepts and techniques for exploring and interpreting data. Participants will learn how to summarise datasets, create visualisations and apply statistical tests using R.
- Refresher in data manipulations and transformations
- Compute summary statistics
- Create univariate and bivariate visualisations
- Learn about populations, samples and random variables
- Explore statistical distributions (Normal, Poisson, Binomial)
- Construct confidence intervals
- Perform hypothesis testing using t-tests, ANOVA, and non-parametric tests
- Build a simple/multiple linear regression model
This course includes a range of activities such as demonstrations, live-coding sessions, interactive quizzes, and practical exercises to work individually or in a group. Active participation and contribution are highly recommended.
At the beginning of the doctorate │ during the doctorate │ at the end of the doctorate
Course participants are expected to have some basic skills in programming with R, for example, attended an “Introduction to R” course or have been coding in R for 3-6 months. This course does not require any previous knowledge of statistics.
Participants should have their own laptop with R, RStudio and the relevant packages installed. Instructions for the technical setup will be circulated by the instructor before the course.
None.
The course will be delivered using Zoom and it will not be recorded.
Dr. Nicolas Attalides is an experienced R programming instructor, an RStudio-certified trainer, and holds a PhD in Statistical Science from University College London. With a background in data science consulting across industries such as insurance and telecommunications, he currently works as a Principal Data Scientist in the private sector. In addition to his industry role, he delivers short courses in R to universities, helping students and professionals develop practical data analysis skills.