Students are expected to attend 3 hours per week of taught sessions: 

  • 2x 1hour lecture
  • 1x 1hour lab 

In addition students will be given:

  • a weekly homework quiz (part of the assessment,
  • a problem set (independent study tasks) and
  • assigned reading.

In total, it is anticipated that students spend approximately 7.5 hours a week on RMS work (inclusive of 3 compulsory hours). More information about how to structure your time can be found in the course Study Guide on LEARN.



The overarching ethic of this course is that methodological training is best provided in regular short sessions, with core skills assessed on regular basis. Importantly, the course focuses on statistical methods as a tool to answering research questions. We will cover the linear model (regression) in detail, with a focus on demonstrating the equivalence of regression and ANOVA. We will also deal with some broader topics and practical issues in data analysis.

In RMS2, we make use of the R statistical programming environment for all labs. Practically, this will develop not only students ability to conduct statistical analyses, but also provide some basic programming skills. Thus, students will develop a suite of highly transferable knowledge and skills.