ECTS credits:

2,5 ECTS (part1) + 2 ECTS (part2)

 

Course parameters:

Language: English

Level of course: PhD course

Time of year: Autumn/ 2021- Spring/2022

No. of contact hours/hours in total incl. preparation, assignment(s) or the like:

This course consists 110 hours consists of preparation hours and discussion & lecture hours.

Part 1 will have 4 input talks and 9 discussion sessions. Part 2 will be 4 input talks and 8 discussion sessions. In total there will be 25 session hours, and 5*17=85 preparation hours.

Capacity limits: 15 participants

 

Objectives of the course: (Apply for both parts)

1. Introduction to Bayesian statistic for researchers in Ecoscience crossing terrestrial and aquatic ecology.
2. Bayesian analysis of simple examples
3. Extending statistic paradigm with Bayesian methods

 

Learning outcomes and competences:

At the end of the part 1, course participants should demonstrate:

• Basic knowledge in Bayesian statistics i(book chapter 1-9)
• Program basic Bayesian statistical methods, including data treatment, Bayesian modelling, visualization and communicate the model results.

At the end of part 2, course participants should demonstrate competences:

• Further knowledge of Bayesian statistics (book chapter 10-17)
• Apply Bayesian programming (R or Python) for research project, model, visualize and communicate your scientific conclusion
• The ability to expand your statistic knowledge based on insights gained in this course

 

Compulsory program:

1. All participants are required to finish the self-study parts before scheduled discussion
2. Each participant will be required to lead one chapter through learning period and facilitate the discussion session.
3. All participants are required to give active participation (active attendance in discussion session and input talk session, active on online discussion forum).
4. Hand in presentations and exercises

 

Course contents:

The main content of this course is to study Bayesian Statistics through book “Statistical Rethinking- A Bayesian Course with Examples in R and Stan” By Richard McElreath, and his online lectures publicly available at https://youtube.com/playlist?list=PLDcUM9US4XdNM4Edgs7weiyIguLSToZRI

The detailed content is in the “course schedule”, with summary and explanation as followed:

1. The whole course is divided into 2 parts due to its heavy content, with first part (chapter 1-9 &online lecture 1-10) running in autumn 2021 and second part (chapter 10-17&online lecture 10-20) running on spring 2022.
2. Participants will self-study the theoretical part of the book, and learn the practical programming each week, and meet every Thursday (physical meeting with online meeting access) for a discussion session.
3. There will be a TEAMs channel (facilitate by AU) for online discussion during the self-study part. Online forum is open for discussion of course and organize own help session with fellow participants or with course instructor.
4. The discussion session will be: 10 min wrap-up of questions left by last session, 10 min presentation of current chapter, 20-25 min discussion on current chapter.
5. Every 4^th week, there will be an input talk either by course instructor or external speakers.

 

Prerequisites:

Entry level of statistics. More important is that the participant need to assign committed hours for studying, attending seminars and being active during study period

 

Name of lecturer: Professor Christian Damgaard, Department of Ecoscience, Aarhus University

 

Type of course/teaching methods:

Seminars (physical and online), self-study (book and online lectures) and online discussion forum

 

Literature:

• Statistical Rethinking (Second Edition)

• Supplementary reading will be provided on need during the course

Course homepage:

None

 

Course assessment:

1.    The individual assignments at the end of each chapter of the book

2.    Lead one chapter of learning, facilitate discussion on discussion session

3.    Bayesian analysis of one own research project

 

Provider:

Department of Bioscience

 

Special comments on this course:

 

1.   The course is flexible regarding ECTS, the students can get 2,5 or 4,5 depending on their depths of learning during this study group.

2.   This course is inspired by the AU Bayes Study group run by Erik Kusch (Ecoinformatics and Biodiversity, Department of biology) in 2020-2021. Erik Kusch provided sufficient input regarding study group design, and is continuously providing input to this course. He is also developing and spreading this methods in his professional career, for more information and some extra materials please visit: https://www.erikkusch.com/project/aubayes/

 

Time: Autumn 2021 –Spring 2022

Seminar once a week, Thursday, lunching meeting, 12-13.

Online communication forum: Teams channel

 

Place:

Vejlsøvej 25, Meeting room M2.04, 8600, Silkeborg (Online Zoom will be available each seminar)

 

Registration:

Please send an e-mail to Fenjuan R. S. Hu, e-mail: frshu@bios.au.dk to sign up for the course. Deadline for registration is 15 August 2021. Information regarding admission will be sent out no later than 18 August 2021.

If you have any questions regarding registration, please contact Fenjuan R. S. Hu, e-mail: frshu@bios.au.dk