An Adventure in Statistics (976C8)

15 credits, Level 7 (Masters)

Autumn teaching

An adventure in statistics consists of a series of lectures and practical classes, mainly aimed at introducing or re-introducing postgraduate students to statistical models. The lectures are aimed at delivering background theory and the practical classes are designed around interactive tutorials that put the theory from the lecture into practice using the open source (and free) statistics software R (implemented in RStudio). Through these tutorials students should develop a good working knowledge of RStudio (and R).

Topics may include:

  • The linear model
  • Key concepts (parameters, estimation, standard error, confidence intervals)
  • Hypothesis testing, effect sizes and Bayes factors
  • Bias and assumptions of the linear model
  • Categorical predictors in the linear model (ANOVA)
  • Factorial designs and covariates
  • Repeated measures designs
  • Multilevel models (HLM)
  • Growth models
  • Categorical outcomes (logistic models)
  • Implementation of the above in R and RStudio


35%: Lecture
65%: Practical


60%: Coursework (Take away paper)
40%: Written assessment (Report)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 39 hours of contact time and about 111 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to COVID-19, staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.