Learning Outcomes:
By the end of this module, students will be able to:
● Apply advanced statistical techniques to psychological data using R and JASP
● Perform data wrangling, visualisation, and programming for efficient and
reproducible analyses.
● Choose, apply and interpret the appropriate statistical model for your dataset.
● Communicate findings effectively through clear and transparent reporting.
Indicative Module Content:
Key Topics Covered:
● Estimation, Probability and Inference
● Transforming raw data into a more usable format. This involves cleaning, structuring,
and enriching data so that it’s ready for analysis (i.e Data wrangling)
● Data visualisation and the grammar of graphics
● Effect sizes and Confidence intervals
● Advanced Regression Techniques: Multiple regression, logistic regression, and
hierarchical regression models
● Linear Mixed-Effects Models: Handling nested and repeated measures data in
psychology
● Introduction to Bayesian inference and applications in psychological research
● Responsible and sustainable use of generative AI to augment data analysis workflows.