The University of Southampton

STAT6086 Survey Methods I

Module Overview

Aims and Objectives

Module Aims

To introduce you to the statistical aspects of the design and analysis of sample surveys. Basic theory underpinning survey inference will be introduced, focussing on methodology for survey-based estimation for population totals and related quantities for some standard sample designs.

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Demonstrate knowledge and understanding of the basic principles underlying survey design and estimation
  • Understand the methods for designing and selecting a sample from a population
  • Estimate finite population parameters, e.g. totals and means, for some standard sampling schemes
  • Assess estimation errors
  • Analyse and solve problems
  • Demonstrate knowledge and understanding of the statistical software STATA


The module takes a design-based approach to inference for survey populations. Topics include: survey estimation strategy, target populations and sampling frames, methods of sampling (probability vs non-probability sampling), simple random sampling, inclusion probabilities, unequal probability sampling, stratified sampling, ratio and regression estimation, systematic sampling, cluster sampling, two-stage sampling.

Learning and Teaching

Independent Study80
Total study time100

Resources & Reading list

W. G. Cochran (1977). Sampling Techniques. 

Software requirements. You will require access to the STATA software, which is available on the University’s computer workstations. Note that this software is not currently available for download to your own computer for use with your studies

C. E. Sarndal, B. Swensson, J. H. Wretman (1992). Model Assisted Survey Sampling. 

Sampling: Design and Analysis. 

Lohr, S. (2010). Sampling: Design and Analysis. 

L. C. Hamilton (2008). Statistics with Stata (Updated for Version 10). 



MethodPercentage contribution
Exam  (2 hours) 100%


MethodPercentage contribution
Exam 100%
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