Postgraduate Course: Core quantitative data analysis 1 and 2 (SCIL11009)
Course Outline
| School |
School of Social and Political Science |
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 |
20 |
| Home subject area |
Postgrad (School of Social and Political Studies) |
Other subject area |
None |
| Course website |
None
|
Taught in Gaelic? |
No |
| Course description |
This web-based course aims to give postgraduate students an understanding of key statistical ideas and methods for social research. The course is designed for students who have little or no previous experience or knowledge of statistics, or even a phobia for numbers, or for those who feel they need a refresher course on the subject. Throughout the emphasis is on learning and understanding by doing, using $ùreal&© data, rather than memorising formulae. The course is divided into two free-standing modules, enabling more advanced students to start at Part 2 (subject to successful completion of preliminary assessment). It is designed to take all students to the level of competence in quantitative data analysis prescribed by the ESRC Research Training Guidelines |
Entry Requirements
| Pre-requisites |
|
Co-requisites |
|
| Prohibited Combinations |
|
Other requirements |
None
|
| Additional Costs |
None |
Information for Visiting Students
| Pre-requisites |
None |
| Displayed in Visiting Students Prospectus? |
Yes |
Course Delivery Information
|
| Delivery period: 2010/11 Semester 1, Available to all students (SV1)
|
WebCT enabled: Yes |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | | 09:00 - 10:50 | | |
| First Class |
Week 1, Wednesday, 09:00 - 10:50, Zone: Central. Seminar Room 1 Crystal Macmillan Building |
| Additional information |
Lectures in weeks 1-10 plus computer based workshops |
| No Exam Information |
Summary of Intended Learning Outcomes
By the end of the course students will:
- Be able to understand and apply a range of quantitative methods and tools
- Understand the logic of statistical description and inference
- Know how to interpret basic statistics
- Have a thorough grounding in descriptive and exploratory data analysis techniques
- Provide a full account of descriptive statistics for 1 and 2 variables
- Understand statistical modelling and be capable of using SPSS for Windows to perform advanced statistical analysis
- Be able to understand and apply multiple linear regression analysis
- Be able to fit and interpret models for categorical dependent variables
- Have experience of working with large data sets
- Understand how to access information about data sources
- Have experience of utilising web-based resources for learning
- Be able to efficiently access IT resources
- Have an understanding of the capabilities of computer software for statistical analysis
|
Assessment Information
| Assessment at the end of part 1 is by means of a multiple choice exam (50%). Assessment at the end of part 2 is by means of a take home exercise (50%). |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Suggested preliminary reading:
Wright D (2002). First Steps in Statistics, Sage, London.
Clegg F (1992). Simple Statistics, Cambridge University Press, Cambridge.
Core text:
Elliot J and Marsh C. (2008) Exploring Data Polity Press, Cambridge.
(Students are encouraged to buy this text)
Fielding J and Gilbert N (2006). Understanding Social Statistics (2nd edition), Sage, London.
Other Recommended texts:
Blalock, H. (1979) Social Statistics (Rev. 2nd ed). Mcgraw Hill New York.
Erickson B and Nosanchuk T (1992). Understanding Data, Open University Press, Buckingham.
Pallant J (2005). SPSS Survival Manual (2nd edition), Open University Press, Buckingham.
de Vaus D (2002). Analysing Social Science data: 50 key problems in data analysis, Sage, London.
de Vaus D (2002). Surveys in Social Research (5th edition), Routledge/Taylor & Francis, London.
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| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords |
Not entered |
Contacts
| Course organiser |
Mr Ross Bond
Tel: (0131 6)50 3919
Email: R.J.Bond@ed.ac.uk |
Course secretary |
Mrs Gillian Macdonald
Tel: (0131 6)51 3244
Email: gillian.macdonald@ed.ac.uk |
|
copyright 2011 The University of Edinburgh -
31 January 2011 8:20 am
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