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Introduction to Bayesian Statistics with R
10 May 2023
08 May 2023
For-profit: 1000 CHF
The course is now full with a long waiting list. But you can still attend the series of long talks on 24 May - free of charge, but registration is mandatory please use this form. **
Overview
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.
Schedule
Day 1 - in person, in Basel
9:00 – 17:00: Jack Kuipers (ETH Zurich and SIB) and Wandrille Duchemin (University of Basel and SIB)
- T-test recap
- P-values and confidence intervals
- Monte Carlo methods
- Bayesian first steps
Day 2 - in person, in Basel
9:00 – 17:00: Jack Kuipers (ETH Zurich and SIB) and Wandrille Duchemin (University of Basel and SIB)
- Bayesian t-tests (STAN + BRMS)
- Priors
- Bayesian linear regression
- Bayesian logistic regression
Day 3 - Long talks and demos - online
- 9:00 – Bayesian foundations of Phylogenetic and Phylodynamic inference – Timothy Vaughan (BSSE-ETHZ and SIB)
- 10:30 - coffee break
- 11:00 - Informative Bayesian priors boost power in genome-wide association studies - Zoltan Kutalik (University of Lausanne and SIB)
- 12:30 Lunch break
- 13:30 - Bayesian approaches in computational biology - Simone Tiberi (University of Bologna and SIB)
- 15:00- coffee break
- 15:30 – Bayesian neural networks – Daniele Silvestro (University of Fribourg and SIB)
- 17:00 Close
Audience
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
Prerequisites
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
Technical
You are required to bring your own laptop and make sure that the following software is installed PRIOR to the course:
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
- BRMS
Application
The registration fees for the 3 full-days for academics are 200 CHF and 1000 CHF for for-profit companies. Day 3 (long talks) is free of charge, but registration is mandatory - in this case, please use this form.
While participants are registered on a first come, first served basis, exceptions may be made to ensure diversity and equity, which may increase the time before your registration is confirmed.
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 01/05/2023 or as soon as the course is full. Deadline for free-of-charge cancellation is set to 08/05/2023. 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 in person only in the Kollegienhauss building of the University of Basel (address: Petersgraben 50, 4051 Basel) on Days 1 and 2, and online only on Day 3.
The course will start at 9:00 and end around 17:00.
More information will be provided to the registered participants one week before the course starts.
Additional information
Coordination: Patricia Palagi
We will recommend 0.75 ECTS credits for this course (given that a successful evaluation is achieved 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 training@sib.swiss.