Lecture Content

Each module is taught by a different lecturer, and the lecturers seem to change every semester/year. 

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Module 1: Data exploration, data sovereignty and statistical inference

In 2025 semester 2, this module was taught by Charlotte Jones-Todd and Jenn Jury, as well as guest lecturer Nicole Edwards. Most students, including me, found this module quite difficult, as it was focused on programming in R, which most people were not familiar with. Although they say that "no coding experience assumed or expected", they do jump straight into it, so be prepared to encounter a lot of unfamiliar terms if you've never coded in your life. They do run R help sessions at the beginning of the semester, and the staff and TAs in the lab are extremely helpful.

 

Charlotte Jones-Todd taught R programming and data exploration. Topics included in this module were:

• R and RStudio: basics, data, debugging

• Data wrangling and manipulation: data analysis, data visualisation and plotting in R

• Introduction to the design and analysis of experiments

• Introduction to hypothesis testing: randomisation tests and p-values

 

Jenn Jury taught statistical inference, in which the topics were covered:

• Hypothesis testing and introduction to linear regression: model assumptions, diagnostic plots

• Statistical inference: predictions, model comparisons and selection 

• Multivariate data analysis: dimension reduction, nMDS

 

There was one lecture on ethical data practices and Māori data sovereignty principles with guest lecturer Nicole Edwards, in which we went over responsible handling of data.

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Module 2: Biological modelling

In 2025 semester 2, this module was taught by Nobuto Takeuchi. This module was more math-based, but integrated with biological context. For example, we did a lot of differentiation and used similar concepts to develop models to explain concepts in biology, like population growth and death. I found Nobuto's teaching style very helpful - he would often have interactive quizzes, go over example questions, and also spend some time recapping the previous lecture. His lectures were supported by interactive H5P activities found on Canvas.

 

The following topics were covered:

• Exponential growth and logarithms

• Growth, death, and resource limitation

• Models: epidemiology, predator-prey

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Module 3: Model-based inference and critical thinking about models

In 2025 semester 2, this module was taught by Emma Carroll. Mant students also found this module challenging as there was a lot of information, alongside some required readings, and it wasn't clear which parts were relevant. However, most of the concepts were conceptual and not too hard to understand.

 

Topics included in this module were:

• Models in science

• Likelihood

• SIR models

• AIC: Akaike Information Criterion

 

Labs

There are 8 labs, each with an associated lab assignment worth 5% (40% total). The labs were based on the lecture content, so it was important to keep up with lectures. They were also very helpful for consolidating lecture concepts. For the most part, the labs were focused on coding in R Studio, as well as interpreting models and graphs.

 

You will work on your lab assignment in the lab, so make sure to ask the TAs any question you have. They are very nice and friendly, and it is also a great chance to ask any questions about lecture content too. Lab assignments range from R script and group discussions, to quizzes and experimental designs.

 

Assessment details

As of 2025, cheat sheets are no longer permitted in stage 2 BIOSCIs and above. Don’t stress out too much though, as the grades achieved without cheat sheets are very similar to those years where cheat sheets were used! 

 

Weekly quizzes

There are 11 assessed weekly quizzes in total starting from Week 2; only 10 with the highest scores are counted to 10% of the total marks.

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In-course Test

The Module 1 test is based on material covered from Module 1 (weeks 1 - 6). It is an on-campus, closed book Inspera-based assessment, with a mixture of multiple-choice and short answer styled questions.

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Exam

The exam is based on material covered from Module 2-3 (weeks 7 - 12). It is in a similar format to the in-course test, online and closed-book, with a mixture of multiple-choice and short answer styled questions.

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Updated: 2025