نظرة عامة على البرنامج

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Introduction to Statistics

Course Information

The course "Introduction to Statistics" is scheduled to take place on:

• Monday, April 20, 2026, from 9:00 AM to 5:00 PM
• Monday, April 27, 2026, from 9:00 AM to 5:00 PM Registration for the course opens on January 21, 2026, at 9:00 AM and closes on March 23, 2026, at 12:00 PM. The course is free of charge and is exclusively available to doctoral candidates of the University of Basel, with a minimum of 6 and a maximum of 25 participants. The trainer for the course is Dr. Jack Kuipers. The course is worth 1 ECTS credit. It is organized by the Graduate Center, focusing on Transferable Skills.

Aims

The primary aim of the course is to provide a hands-on introduction to statistical analyses, covering foundational statistical concepts and techniques. Upon completing the course, participants will be able to:

• Explore and describe data
• Code and run analyses in R
• Understand and implement basic statistical models
• Interpret results from statistical analyses The course emphasizes practical applications and conceptual understanding through simulation-based and interactive learning materials.

Content

The course content includes:

• How to code with R to handle data and run analyses
• Descriptive statistics and how to compute and visualize them
• Elementary inferential statistics: sampling distributions, confidence intervals, p-values, and hypothesis testing
• Basics of statistical modeling to describe relationships between variables

Methods

The course combines self-study workbooks to introduce R programming, instructor-led interactive sessions for introducing concepts, hands-on exercises for practical application, and home assignments to reinforce skills.

Target Group

The course is designed for all doctoral candidates.

Requirements

Participants are required to have a computer with R and Rstudio installed. The pre-course material covers R programming and needs to be completed before the in-person sessions. This material will also include installing relevant R packages.

About the Trainer

Dr. Jack Kuipers is a lecturer and senior scientist at the D-BSSE of the ETH Zurich. His research areas include computational oncology and computational statistics, with an emphasis on probabilistic graphical models for complex high-dimensional data and their application to tumor evolution. He holds a PhD from the School of Mathematics at the University of Bristol and has extensive experience in method development, data analysis, and teaching introductory statistics.

Workload

The total workload for the course is 30 hours, consisting of:

• 8 hours of self-study for the pre-course material covering R programming
• 16 hours of learning over two days, including practical work
• Additional assignments each week taking 3 hours to complete as part of the course
• 3 hours for other activities

Feature

Once registration is open, applications will be collected for 24 hours, and course places will be allocated by lot. All registrations received after the initial 24-hour period will be put on a waiting list and assigned on a first-come, first-served basis. Course places or places on the waiting list will be confirmed by email. Full course attendance is mandatory. Participants who fail to attend a course without prior notification or withdraw after the registration deadline are subject to a fee. Detailed regulations can be found on the Transferable Skills Homepage.

Location

The course will take place at the University of Basel, Steinengraben 22, 4001 Basel, in Seminarraum 011.