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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2014/2015
- ARCHIVE as at 1 September 2014

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DRPS : Course Catalogue : School of Philosophy, Psychology and Language Sciences : Psychology

Postgraduate Course: Multivariate Statistics and Methodology using R (PSYL11054)

Course Outline
SchoolSchool of Philosophy, Psychology and Language Sciences CollegeCollege of Humanities and Social Science
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaPsychology Other subject areaNone
Course website None Taught in Gaelic?No
Course descriptionThe 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites It is RECOMMENDED that students have passed Statistics (DENT11001) OR Univariate Statistics and Methodology using R (PSYL11053) OR Algebra (MATH10021)
Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?No
Course Delivery Information
Delivery period: 2014/15 Semester 2, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 12/01/2015
Breakdown of 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 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 0 %, Coursework 0 %, Practical Exam 100 %
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
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
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus 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.
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsNot entered
Contacts
Course organiserDr Thomas Booth
Tel: (0131 6)50 8405
Email: Tom.Booth@ed.ac.uk
Course secretaryMiss Toni Noble
Tel: (0131 6)51 3188
Email: Toni.noble@ed.ac.uk
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