Postgraduate Course: Core quantitative data analysis for social research: part 1 (PGSP11078)
Course Outline
| School | School of Social and Political Science |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The course introduces key statistical ideas and methods for social and political research. It 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. The emphasis is on learning and understanding by doing, using 'real' data, rather than memorising formulae or rules of procedure. Each online learning module is supplemented by self-tests and activities to give students practice in the exploration and analysis of quantitative data using the SPSS software package, copies of which may also be provided free of charge to students for use on their own personal computers. In line with ESRC postgraduate research training guidelines, the aim of the course is to ensure that students are able to understand and use basic quantitative methods.
The course focuses on exploratory and descriptive data analysis. It considers the theoretical basis for using numbers in social research and examines the production and interpretation of tables as a way of presenting empirical evidence. It introduces fundamental concepts and areas such as cases, variables and values; levels of measurement; the graphical representation of data; measures of central tendency and dispersion; and patterns of causality in three or more variables.
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| Course description |
Introduction to quantitative data analysis; Levels of measurement; Discrete and continuous variables
Summarising data: Measures of spread and central tendency; Presenting data in table and charts
Relationships between variables: correlation, association and causation; simple linear regression
Measures of association; Modelling nominal and ordinal variables
Relationships between more than two variables: controlling for a third variable
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2015/16, Available to all students (SV1)
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Quota: 10 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Seminar/Tutorial Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
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| Additional Information (Learning and Teaching) |
Course organiser now Ross Bond
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
One multiple choice exam. |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the links between theory and method, including the potential and limitations of quantitative evidence
- Understand and have a thorough grounding in exploratory and descriptive data analysis
- Understand how to use computer software for statistical analysis of large datasets
- Understand and apply simple bivariate regression analysis
- Communicate statistical evidence through graphs, tables and text
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Reading List
Elliot J. and Marsh C. (2008) Exploring Data (2nd edition), Cambridge: Polity.
Fielding J. and Gilbert N. (2006) Understanding Social Statistics (2nd edition), London: Sage.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
Students intending to take Core Quantitative Data Analysis parts 1 AND 2 should register for the 20 credit course (SCIL11009). |
| Keywords | Not entered |
Contacts
| Course organiser | Prof Andrew Thompson
Tel: (0131 6)51 1562
Email: |
Course secretary | Mr Andrew Macaulay
Tel: (0131 6)51 5067
Email: |
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