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The University of Southampton

STAT6093 Survey Sampling

Module Overview

To provide an overview of basic sampling and estimation methods. One of the pre-requisites for STAT6091 and STAT6094

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Demonstrate knowledge and understanding of the basic methods in common use for sampling from finite populations, including the most common sampling designs, and how to estimate finite population parameters and how to assess the estimation errors


The course is divided into the following main topics: • Introduction: need for samples, terminology, notation, estimation strategy, survey errors, probability sampling • Simple random sampling (with and without replacement): probability functions, central limit theorem, bias of estimators, inclusion probabilities, standard errors, finite population correction, variance estimation, confidence intervals, proportions, domains, ratio estimation • Unequal probability sampling: Horvitz-Thompson estimator, design based inference • Stratified sampling: estimation, variance estimation, sample allocation, post-stratification • Systematic sampling: estimation, variance estimation • Multi-stage sampling: cluster sampling (equal and unequal size), estimation, variance estimation, design effects, sample size allocation

Learning and Teaching

Teaching and learning methods


Independent Study70
Total study time100

Resources & Reading list

Lohr, S.L. (1999). Sampling Design and Analysis. 

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



MethodPercentage contribution
Exam  (2 hours) 100%


MethodPercentage contribution
Exam  (2 hours) 100%

Repeat Information

Repeat type: Internal & External

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