Module overview
This module will expose you to current theory in survey inference, focusing on methodology for survey based estimation for population totals and related quantities.
Linked modules
Pre-requisite: STAT6093 AND STAT6095
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- evaluate the uncertainty associated with an estimation method.
- understand the differences between design-based and model-based approaches to sample survey estimation;
- assess the advantages and disadvantages of an estimator with respective to the underlying model assumptions and the sampling design;
- apply the estimation methods in common use of survey sampling;
Syllabus
- Historical overview.
- Design-based survey estimation.
- Conceptual problems of design-based inference.
- Model-assisted survey estimation (post-stratification, ratio estimation, regression estimation).
- Model-based survey estimation.
- Variance estimation.
Learning and Teaching
Teaching and learning methods
A variety of methods will be used including lectures and workshops/tutorials, mixed in a 5 day course designed for students on release from the workplace. Students are also expected to read wider than the lecture material as part of their individual study, and to critically appraise different approaches.
Type | Hours |
---|---|
Teaching | 25 |
Independent Study | 75 |
Total study time | 100 |
Resources & Reading list
Journal Articles
Deville,J.-C. and Sarndal,C.-E (1992). Calibration Estimators in Survey Sampling.. Journal of the American Statistical Association, 87, 376-382.
Textbooks
Cochran, W.G (1977). Sampling Techniques. New York: Wiley.
Valliant, R., Dorfman, A.H. and Royall, R.M. (2000). Finite Population Sampling and Inference. New York: Wiley.
Chambers, R.L. and Clark, R.G. (2012). An Introduction to Model-Based Survey Sampling with Application. Oxford: OUP.
Sarndal, C.-E., Swensson, B. and Wretman, J (1992). Model Assisted Survey Sampling. New York: Springer-Verlag.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Repeat Information
Repeat type: Internal & External