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Students must attend 3 hours per week of compulsory taught sessions. Each week students will attend:

  • 2x 1hour lecture
  • 1x 1hour lab (students will register for one of four possible slots)

In addition students will have a weekly homework quiz, a guided lab SWIRL, a problem set 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. The course provides a thorough grounding in the basics of probability and statistical data analysis for psychologists. Importantly, the course focuses on statistical methods as a tool to answering research questions. We will cover the basics of probability and probability distributions; fundamentals of statistical hypothesis testing; and core statistical tools including chi-square, t-tests, correlation and simple linear regression models.

In RMS, 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.