Course Structure

Compulsory Core Modules (50 credits)

• Questionnaire Design (5 credits) - [sample notes]
• Sampling Design (5 credits) - [sample notes]
• Secondary Data Analysis (5 credits) - [sample notes]
• Statistical Inference (15 credits) - [sample notes]
• Generalized Linear Models (10 credits) - [sample notes]
• Multi-level Models (10 credits) - [sample notes]

Optional Modules (70 credits)

Students take a selection from the following 14 optional modules to make up 70 credits. Students may choose any module that is of interest to them. The designated specialist pathways provide a suggested structure for those with particular professional interests. Please note that not all options may be offered each year:

• Duration (Survival) Analysis (10 credits) - [sample notes]
• Bayesian Methods (10 credits) - [sample notes]
• Methods for Missing Data (10 credits) - [sample notes]
• Structural Equation Modelling (10 credits) - [sample notes]
• Data Mining Techniques (10 credits) - [sample notes]
• Statistics in Practice (10 credits) - [sample notes]

• Quantifying and Evaluating Forensic Evidence (10 credits)
• Quantitative Criminology (10 credits)
• Event History Analysis (10 credits)

Statistical Methods for Health Research pathway:

• Principles of Epidemiology (10 credits)
• Clinical Trials (10 credits)

• Teaching Statistics (60 credits; a distance learning module)

Support Courses

• Methodological Debates (non credit) - [sample notes]
• Mathematics for Statistics (non credit) - [sample notes]

• Statistical Methods (non credit) - [sample notes]

Software Courses

• Atlas.ti - [sample notes]

• R (compulsory module) - [sample notes]
• SPSS for Windows: I - [sample notes]
• SPSS for Windows: II - [sample notes]
• STATA  (desirable) - [sample notes]

Dissertation (60 credits)

• Dissertation (60 credits)

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