Module Details

SC971-7-SP-CO: Applied Sampling

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Year: 2016/17
Department: Sociology
Essex credit: 20
ECTS credit: 10
Available to Study Abroad / Exchange Students: Yes
Full Year Module Available to Study Abroad / Exchange Students for a Single Term: No
Outside Option: No

Supervisor: Dr Tarek Albaghal
Teaching Staff: Dr Tarek Albaghal; Professor Peter Lynn (ISER)
Contact details: Michele Hall, Graduate Administrator, Telephone 01206 873051, Email:

Module is taught during the following terms
Autumn Spring Summer

Module Description

Applied Sampling is an applied statistical methods course that focuses on the design of probability samples to be used for data collection. Sample designs are driven by analytic goals of an investigator, but this is not an analysis course. In particular, this course focuses on the principles of designing and selecting samples of individuals. This course will focus on sampling populations of humans because of the unique challenges posed by such populations. This will include both methods for sampling the general population and methods for sampling specialist or minority populations, including screening methods and two-phase sampling. Sampling techniques covered will include simple random sampling, stratification, cluster sampling, systematic sampling, multistage sampling, probability proportional to size sampling, and flow sampling. Applications of these methods for face-to-face interview surveys, telephone surveys and self-completion surveys will be examined. Cost, sampling frames, and sampling error estimation techniques will also be addressed.


To provide a practical introduction to methods of survey sampling and estimation.

Learning Outcomes

By the end of the module students should:

    1. Understand fundamental characteristics of different sample designs.
    2. Recognise the strengths and weaknesses of alternative proposed designs for a particular survey
    3. Be able to apply techniques for sample design and sample selection.
    4. Be familiar with statistical notation and formulas for different sample designs.
    5. Understand and be able to estimate the effects of sample designs on survey estimates.
    6. Be able to design and describe, in writing, a multistage probability sample of a population.


  • Principles in sample selection

  • Sampling frames and frame problems

  • The methodology to draw samples and estimate correct measures of central tendency and variation using the following sampling techniques:

  • Simple random sampling

  • Stratified sampling

  • Cluster sampling

  • Complex (stratified, multi-cluster) sampling

  • Systematic sampling

  • Probability proportionate to size sampling

  • The calculation of design effects, the variance inflation factor

  • Introduction to advanced variance estimation techniques

Learning and Teaching Methods

20 contact hours (2 per week for 10 weeks). Primarily lecture-based, with some practical sessions.


100 per cent Coursework Mark


The module is assessed with a combination of bi-weekly course work (counting for 50% of the final grade) and a final project 4000 words (counting for 50%)

Other information

18 hours in Spring Term 2 hr lecture (or 1hr lecture and 1 hr lab) each week.

Prerequisites: Survey Methods I; SC504 or equivalent

Compulsory for: MSc Survey Research and Methods for Social Research students


  • Supplementary
  • Groves, Robert M., Floyd J. Fowler, Jr., Mick P. Couper, James M. Lepkowski,
  • Eleanor Singer, Roger Tourangeau (2004), Survey Methodology, Wiley (chapters 2, 3, 4)
  • Kish, Leslie. Survey Sampling. 1965. John Wiley and Sons, Inc.: New York.
  • Lynn, P.(2002) 'Principles of sampling'. Chapter 23 (185-194) in T. Greenfield (ed.),
  • Research Methods for Postgraduates (2nd ed). London: Arnold
  • Lynn, P.(2002) 'Sampling in human studies'. Chapter 24 (195-201) in T. Greenfield (ed.), Research Methods for Postgraduates (2nd ed). London: Arnold
  • Stuart, A. (1984) The Ideas of Sampling. High Wycombe: Griffin.
  • Week by week specific readings will be provided at the beginning of the term.

Further information