MSc Data Science (Social Analytics) / Course details
Year of entry: 2021
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Course unit details:
Complex Survey Designs and Analysis
|Unit level||FHEQ level 7 – master's degree or fourth year of an integrated master's degree|
|Teaching period(s)||Semester 2|
|Offered by||Social Statistics|
|Available as a free choice unit?||Yes|
The students should have some familiarity with survey research and statistical modelling. A pre-requisite of the course is: Introduction to Statistical Modelling (ISM - SOST70011).
This course provides an insight into the design and methodological issues for the analysis of complex surveys. It also introduces analytical methods and software for handling complex survey datasets.
At the end of this module, students should be able to:
- Understand methodological concepts in survey design, estimation and adjusting for nonresponse.
- Assess the strengths and weaknesses of complex survey designs and the resultsing secondary survey data.
- Assess how aspects of survey design will impact on the analysis.
- Use STATA (and other) software to analyse complex survey data.
- Understand the difference between model-based and design-based approaches to handling complex survey designs.
Teaching and learning methods
3 hour lectures online and on campus
|Written assignment (inc essay)||85%|
The assessment for this module will be based on an online multiple-choice test (15%) and one piece of coursework of 3,000 words (85%).
Blair, J., Czaja, R. and Blair, E. (2014) Designing Surveys: A Guide to Decisions and procedures, 3rd edition. CA: Sage Publication.
Heeringa, S. G., West, B. T, & Berglund, P. A. (2010). Applied Survey Data Analysis. Boca Raton: CRC Press.
Lehtonen, R. and Pahkinen, E.J. (2004) Practical Methods for Design and Analysis of Complex Surveys, 2nd edition. Chichester: John Wiley & Sons.
Lohr, S.L. (2009) Sampling: Design and Analysis, 2nd edition. Boston: Brooks/Cole.
Snijders, T.A.B. & Bosker, R.J. (2012) Multilevel analysis: An Introduction to Basic and Advanced Multilevel Modelling, 2nd edition. London: Sage.
|Scheduled activity hours|
|Independent study hours|
|Maria Pampaka||Unit coordinator|
Compulsory for SRMS
Part time students must take ISM prior to CSDA
Week 1-4: Wednesday 9-12 & Thursday 9-12
Week 8 & 9: Thursday 9-12