PSYC3697: Statistical Modelling
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Type | Open |
---|---|
Level | 3 |
Credits | 10 |
Availability | Available in 2024/2025 |
Module Cap | 50 |
Location | Durham |
Department | Psychology |
Prerequisites
- 10 credits from Level 2 Psychology
Corequisites
- Advanced Research Methods and Statistics
Excluded Combinations 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 | Monitored |
---|---|---|---|---|---|
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
More information
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