This course provides an overview of basic statistical modelling for the analysis of psychological data. 

Weekly one-hour lectures

None

None

Two 1-hour practical skills assessments, each worth 50% of the total grade, occurring at the midpoint and end of the semester.

Reassessments are normally available for all courses, except those which contribute to the Honours classification. For non Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

To teach students a conceptual understanding of basic statistical modelling approaches to the analysis of psychological data and the practical skills to apply these approaches and interpret statistical output.

By the end of this course students will be able to:

■ Integrate knowledge about study design and statistics to formulate and estimate the General Linear Model (GLM) appropriate to the various types of study designs encountered in psychology

■ Visualise and interpret various effects (including interactions) in multi-way designs.

■ Estimate linear mixed-effects models and describe their relation to traditional techniques such as ANOVA and multiple regression.

■ Formulate and estimate path models and interpret the statistical output.

■ Perform logistic regression and explain and interpret the statistical output.

■ Create reproducible data analysis scripts and reports within the R statistical programming environment.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.