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 |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Psychology |
Other subject area | None |
| Course website |
Please use Learn |
Taught in Gaelic? | No |
| Course description | The semester long course provides an Advanced level examination 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 is suitable for students following Masters programmes in Psychology and Linguistics
R is a language and environment for statistical computing and graphics, based on the S language. R is a flexible and increasingly popular package 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 statistical method to use and b) that all statistical methods are special cases of a more general model. This course focuses on research in which 2 or more outcome variables are being studied simultaneously
Typical Syllabus
- Fundamentals of matrix algebra
- Fundamentals of calculus and maximum likelihood estimation
- Multilevel modeling I
- Multilevel modeling II
- Multilevel modeling III
- Multilevel modeling IV
- Factor analysis I
- Factor analysis II
- Factor analysis III
Taught by Wendy Johnson, Antje Nuthmann, and Tom Booth.
Formative feedback available;
- Lab assignments throughout the semester |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
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| Delivery period: 2013/14 Semester 2, Available to all students (SV1)
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Learn enabled: Yes |
Quota: None |
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Web Timetable |
Web Timetable |
| Class Delivery Information |
+ one hour |
| Course Start Date |
13/01/2014 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 33,
Feedback/Feedforward Hours 1,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
64 )
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| Additional Notes |
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| Breakdown of Assessment Methods (Further Info) |
Written Exam
0 %,
Coursework
0 %,
Practical Exam
100 %
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| No Exam Information |
Summary of Intended 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. |
Assessment Information
Analyses of a data set
Assignment deadline: Monday 21st April 2014, 12 noon
Page limit: 2 pages of A4 with 2 cm margins, double spacing, and with no bigger than 11 point Times New Roman font. One additional side of A4 can be used for tables, figures, etc. There is no font size limit but markers need to be able to read legends, etc.
Return deadline: Tuesday 13th May 2014 |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Alexander Weiss
Tel: (0131 6)50 3456
Email: alex.weiss@ed.ac.uk |
Course secretary | Miss Toni Noble
Tel: (0131 6)51 3188
Email: Toni.noble@ed.ac.uk |
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