Introduction to Bayesian statistics with R

Date 28 - 30 November 2022
Speaker(s) Jack Kuipers, Wandrille Duchemin, Zoltan Kutalik, Simone Tiberi, Timothy Vaughan
ECTS 0.75
Fees *academic: 120 CHF   -   for-profit: 600 CHF
Cancellation deadline 14 Nov 2022
City Basel
*academic fee includes non for-profit organisations as well as unemployed participants at the time of application.

The course is now full with a long waiting list. But you can still register to Day 3 (long talks), which is free of charge, but registration is mandatory please use this form to register.


Data analysis is fundamental for arriving at scientific conclusions and testing different model hypotheses. Key to this is understanding uncertainty in our results, and Bayesian statistics offers a framework to quantify and assess the variability in our inference from data. This 3-day course will introduce participants to the core concepts of Bayesian statistics through lectures and applied examples. The first two days of the course will be dedicated to lectures and practical exercises. The practical exercises will be implemented in the widely used R programming language and the Rstan library. They will enable participants to use standard Bayesian statistical tools and interpret their results.

The third day will host a series of talks by experts from SIB groups, who will present state-of-the-art Bayesian methods and their application in the life sciences.

Preliminary program

Day 1 - in person, in Basel

9:00 – 17:00: Jack Kuipers (ETH Zurich and SIB) and Wandrille Duchemin (University of Basel and SIB)

  • From the t-test to Monte Carlo integration
  • Probability and Bayes theorem
  • Prior and posterior distributions
  • Markov Chain Monte Carlo (MCMC) basics

Day 2 - in person, in Basel

9:00 – 17:00: Jack Kuipers (ETH Zurich and SIB) and Wandrille Duchemin (University of Basel and SIB)

  • STAN – a platform for (easy) Bayesian statistical modelling
  • Bayesian regression models using Stan (BRMS)
  • Bayesian linear regression

Day 3 - online

9:00 – 17:00: A series of three long talks and demos:

  • 9:00 – Bayesian approaches in computational biology - Simone Tiberi (University of Zurich and SIB)
  • 11:45 - Informative Bayesian priors boost power in genome-wide association studies - Zoltan Kutalik (University of Lausanne and SIB)
  • 12:30 Lunch break
  • 13:30 - A Bayesian approach to learn whole genome genetic architecture and causal effects - Zoltan Kutalik (University of Lausanne and SIB)
  • 14:30 – Bayesian foundations of Phylogenetic and Phylodynamic inference – Timothy Vaughan (BSSE-ETHZ and SIB)
  • 17:00 End


This course is intended for life scientists familiar with statistical inference and who would like to add the Bayesian perspective to enrich their research.

Learning outcomes

At the end of the course, participants should be able to:

  • Recognise the core components of a Bayesian model
  • List the main concepts of methods for Bayesian inference
  • Implement a simple Bayesian model in R
  • Interpret the results of a Bayesian model


Knowledge / competencies

Being at ease with R is absolutely required for this course (at least equivalent to the First steps with R SIB course). Basic knowledge of statistical inference (for instance, equivalent to the Introduction to statistics SIB course) is also required.

Both pre-requisites are also taught by the ETHZurich course introduction to statistics and R


You are required to bring your own laptop and make sure that the following software is installed PRIOR to the course:

  • A recent verion of R and RStudio (the free version is more than enough).

Additionally, make sure to have the following R libraries installed:

  • The Rstan package (warning, there are 2 steps to the installation: Configuring C++ toolchains, and then installation of Rstan)
  • Rmarkdown
  • Shiny
  • tidyverse


The registration fees for the 3 full-days for academics are 120 CHF and 600 CHF for for-profit companies (Apply button at the bottom of this page). Day 3 (long talks) is free of charge, but registration is mandatory - in this case, please use this form.

You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.

Applications close on 11/11/2022. Deadline for free-of-charge cancellation is set to 14/11/2022. Cancellation after this date will not be reimbursed. Please note that participation in SIB courses is subject to our general conditions.

Venue and Time

This course will be at the University of Basel on Days 1 and 2, and online on Day 3.

The course will start at 9:00 and end around 17:00.

More information will be provided to the registered participants in due time.

Additional information

Coordination: Patricia Palagi

We will recommend 0.75 ECTS credits for this course (given a passed exam at the end of the course).

You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.

Please note that participation in SIB courses is subject to our general conditions.

SIB abides by the ELIXIR Code of Conduct. Participants of SIB courses are also required to abide by the same code.

For more information, please contact