Introduction to sampling

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Introduction to sampling

Introduction to sampling

This is an introductory course on sampling (in French), published by the MIA department of the INRA: http://www.inra.fr/mia/ The objective of the course is to give some notions on different classical sampling designs aimed at estimating a simple parameter (here the average of a random variable), and the necessary knowledge to choose the most adapted sampling strategy in a given context.

It is structured around:

  • Definitions of sampling processes, illustrated by examples
  • A catalogue of classical sampling designs with their advantages and disadvantages:
    • Inventories
    • Sampling: simple random sampling, systematic sampling, stratified random sampling, random cluster sampling, multi-stage sampling, multiple sampling occasions, sequential sampling, distance sampling, capture-recapture sampling.

A program allows to simulate samplings on test-populations. You can thus evaluate the variability of an estimator, compare the four most common methods, find the most adapted one for each example and calculate, by simulation, the average and the variance of the estimator associated to each sampling.

Authors: Bruchou C., Chabanet C., Gasqui P., Hommay G., Hulmel M., Kervelle J., Membre J-M., Moisan A., Pierrat J-C., Sauvard D., Vaillant J.

You can download the course HERE

Modification date : 25 April 2023 | Publication date : 16 September 2013 | Redactor : IPM network, contributor: Olivier DAVID (INRA).