An Adventure in Statistics (976C8)
15 credits, Level 7 (Masters)
Autumn teaching
On this module, you’ll explore statistical models.
You’ll put your theory into practice through interactive classes, using the open-source statistics software R (implemented in RStudio). Through these tutorials, you’ll develop a good working knowledge of RStudio and R.
Topics include:
- the linear model
- key concepts including parameters, estimation, standard error and 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.
Teaching
35%: Lecture
65%: Practical
Assessment
55%: Coursework (Take away paper)
45%: Written assessment (Report)
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鈥檙e planning to run these modules in the academic year 2025/26. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.
We鈥檒l make sure to let you know of any material changes to modules at the earliest opportunity.