BEES3041 - Statistics in Life and Environment

“BEES3041- Big Data in the BEES” is a brand new course wherein students work as a real data scientist, i.e. someone who can effectively analyse, interpret and present real and often challenging data (using, for example, R, RStudio and RMarkdown).

Term 2

6 Units of Credit




What do I do in this course?

The course runs over 10 weeks. In the first 3 weeks, students will attend a mix of lectures and practicals on 5 different topics. In the remaining 7 weeks, students conduct a research project, supervised by one of the course lecturers. This involves attending a weekly tutorial, to update supervisors about their project, and producing a research proposal, presentation and project paper. The course assessment will be based on these 3 assignments.

The topics of the lectures and practicals could include:

○   Systematic reviews, meta-analysis and meta-research

○   Geographic data analysis and mapping

○   Phylogenetic methods (building phylogenetic trees, or applying comparative methods)

○   Modelling the dynamics of systems (populations, climate, genetics)

○   Computational simulations of biological worlds


 Who are we, and who should I contact?

The course will be taught by:

○  A/Prof Will Cornwell

○  Dr Martin De Kauwe

○  Dr Daniel Falster

○  A/Prof Shawn Laffan

○  Prof Shinichi Nakagawa

○  Dr Sarah Perkins-Kirkpatrick

Contact – Course Coordinator: Prof Shinichi Nakagawa

Current handbook entry

 Current timetable

 Course Outline


Where does this course fit into my degree?

This course is intended for 3rd-year students and will run in Term 2 (see UNSW3+ schedule:

If you are planning to do honours, this course is highly recommended. The skills you learn from BIOS3041 will make you a top honours student

Is there assumed prior knowledge or a co-requisite?

A pre-requisite is at least 48UoC completed. 


Is there anything else I should know?

You will being conducting a (small) research project with world-leading scientists while learning about how to carry out research. This will be totally rewarding!

Check out this web site of Environmental Computing (]). While we assume some working knowledge in R, you will master many of topics covered in this web site.