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 |
The course will cover descriptive and exploratory data analysis principles of inference, measures of association and elementary multivariate analysis. Course content will include: the structure of social science data - cases, variables, values, data sets and missing data; levels of measurement, univariate data analysis including frequency distributions and the graphical representation of data; measures of central tendency, dispersion and variability; normal distribution, standard scores and regrouping variables; distributions and confidence intervals and population variance; hypothesis testing and significance tests; tabular data and measures of association between categorical variables, correlation and regression; the use and interpretation of multivariate data and data management and analysis using statistical software (SPSS).
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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 |
Not entered |
| 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 -
13 January 2011 6:44 am
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