Postgraduate Course: Multivariate Statistics and Methodology using R (PSYL11054)
Course Outline
| School | School of Philosophy, Psychology and Language Sciences |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The semester long course provides an advanced level overview of a variety of statistical analysis techniques and methodology issues relevant to psychological research. It is taught using a combination of lab and lecture sessions and focusses on techniques used by students following Masters programmes in Psychology and Linguistics and researchers practicing in these areas.
R is a language and environment for statistical computing and graphics that is highly flexible and increasingly popular for statistical analysis. It provides a wide variety of statistical and graphical techniques, including facilities to produce well-designed publication-quality plots.
Design and analysis are taught under a unifying framework which shows a) how research problems and design should inform which specific statistical method to use and b) that all statistical methods are special cases of a more general model. This course focuses on situations in which 2 or more outcome variables are being studied simultaneously.
The course is co-taught between Dr Tom Booth and Dr Antje Nuthmann.
Formative feedback available:
- Lab practicals that provide direct feedback on exercises and queries.
- Q&A sessions held once a week with course TAs.
- Model answers for all lab and homework exercises. |
| Course description |
Typical Syllabus
- Estimation methods
- Multilevel modelling (4 lectures)
- Introduction to matrix algebra for statistics
- Principal components analysis
- Factor analysis (exploratory and confirmatory)
- Introduction to structural equation modelling
A detailed week by week syllabus will be provided prior to the start of the course.
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Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
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| Academic year 2014/15, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 20,
Supervised Practical/Workshop/Studio Hours 20,
Feedback/Feedforward Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
48 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
0 %,
Practical Exam
100 %
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| Additional Information (Assessment) |
End of course assignment: a data analysis exercise (take home exam) 100%.
Page limit: 6 pages for the write-up (2 pages of text and 4 pages of tables/figures). The report should be written in a standard font, size 12, with standard 1 inch (2.54cm) margins on all sides. There is no limit for the R-code which will be submitted alongside the report.
Assignment deadline: Monday 20th April 2015, 12 noon
Return Date: 12th May 2015
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
1. Understand a variety of issues regarding the choice of statistical analysis techniques for standard and unusual data sets.
2. Understand how to use the R language as a tool for data manipulation, analysis and graphics.
3. Become adept in expressing statistical models typically used in psychological research and interpreting their results.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Thomas Booth
Tel: (0131 6)50 8405
Email: Tom.Booth@ed.ac.uk |
Course secretary | Miss Toni Noble
Tel: (0131 6)51 3188
Email: Toni.noble@ed.ac.uk |
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