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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014
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DRPS : Course Catalogue : School of Philosophy, Psychology and Language Sciences : Psychology

Postgraduate Course: Advanced statistical methods for psychology using R (PSYL11040)

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 course provides an advanced level examination of a variety of statistical analysis techniques and methodology issues relevant to psychological research. The course gives students an introduction to R, 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.

The environment is highly extensible, and is increasingly being adopted as the platform of choice for research in statistical methodology and in modern applied statistics in the social sciences, including psychology (see: Social Sciences and Graphics at http://cran.r-project.org/src/contrib/Views/).

Lecture sessions are designed to give students an overview and introduction to the individual methodologies. These will be supplemented by Lab sessions which will give students extensive practical experience of working with a highly interactive statistical package.

The course comprises ten seminar and lab sessions. A typical syllabus would include:
1. Research with children and special groups
2. Qualitative approaches to data analysis
3. Single case studies.
4. Introduction to the R statistical programming language: data manipulation and re-shaping.
5. Statistical graphics.
6. Descriptive and inferential statistics. (usually including t-tests, non-parametric tests, chi-squared and correlations).
7. Power analysis.
8. Modelling I: regression, ANOVA.
9. Modelling II: mixed-effects, SEM.
10.Exploratory factor analysis
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesStudents should have a background in basic statistical techniques.
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Not being delivered
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
A Data Analysis Exercise. This will comprise the analysis of a given set of data and presentation of results. The analysis should be performed and then written in the style of a results section of a journal article with commentary. Word limit: approximately 3000 words.
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
KeywordsNot entered
Contacts
Course organiser Course secretaryMiss Toni Noble
Tel: (0131 6)51 3188
Email: Toni.noble@ed.ac.uk
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