An Adventure in Statistics (976C8)

15 credits, Level 7 (Masters)

Autumn teaching

This module consists of a series of lectures and practical classes, mainly aimed at introducing or re-introducing you to statistical models.

The lectures are aimed at delivering background theory, while the practical classes are designed around interactive tutorials that put the theory from the lecture into practice using the free, open source statistics software R (implemented in RStudio).

Through these tutorials you 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
• gategorical outcomes (logistic models)
• implementation of the above in R and RStudio.

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 40 hours of contact time and about 110 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 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.

We’ll make sure to let you know of any material changes to modules at the earliest opportunity.