Undergraduate Programme and Module Handbook 2024-2025
Module PSYC3697: Statistical Modelling
Department: Psychology
PSYC3697: Statistical Modelling
| Type | Open | Level | 3 | Credits | 10 | Availability | Available in 2024/2025 | Module Cap | 50 | Location | Durham |
|---|
Prerequisites
- • 10 credits from Level 2 Psychology
Corequisites
- • Advanced Research Methods and Statistics
Excluded Combination of Modules
- • None
Aims
- To teach students a set of advanced statistical methods that are used across psychology, neuroscience and the behavioural sciences
- To provide students with the capacity to confidently identify appropriate statistical techniques and analyse data using relevant software across a range of different types of research
Content
- Indicative content as follows:
- Modelling in R
- Linear models
- Logistic regression and general linear models
- Multi-level modelling
- Structural equation modelling
- Multidimensional scaling and cluster analysis
- Meta-analysis
Learning Outcomes
Subject-specific Knowledge:
- On completion of this module, students will acquire knowledge and understanding of:
- A range of advanced statistical tests used in psychology, neuroscience and the behavioural sciences
- The assumptions and limitations of the statistical techniques covered
- The advantages and limitations of using different statistical software (e.g., R, JASP)
Subject-specific Skills:
- By the end of the module students should be able to:
- Use and apply a range of advanced statistical techniques used in psychology, neuroscience and the behavioural sciences
- Effectively use statistical applications software (e.g. R, JASP)
- Analyse data accurately
- Interpret data appropriately >
Key Skills:
- Good written communication skills
- Good IT skills in word processing
- Ability to work independently in scholarship and research within broad guidelines
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Student understanding and practical ability to use the statistical tools will be facilitated by workshops supplemented with online material.
- Students will watch online lectures asynchronously and on their own time study the theoretical material
- The workshops will take place in a computer laboratory, where students will get experience in using the statistical tools
- The weekly summative examination assesses students' acquired knowledge of theoretical principles through the weekly online test
- The summative reports will assess students' ability to use the methods in practice, working on a small secondary data set
- Formative tests will be given in class to prepare students for all summative tests
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Workshops | 5 | Every 2 weeks | 2 hours | 10 | |
| Lecture (online) | 10 | 1 per week | 1 hour | 10 | |
| Preparation and Reading | 80 | ||||
| Total | 100 |
Summative Assessment
| Component: Summative Report | Component Weighting: 90% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Statistics Report | 50% | ||
| Statistics Report | 50% | ||
| Component: In Class Tests | Component Weighting: 10% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| In Class Tests | 8 x 5 Minutes | 100% | |
Formative Assessment:
The formative assessment will be undertaken in class and feedback will be provided. Students will be set short-answer questions which might include being provided with secondary quantitative data sets to analyse and interpret.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University