Survey and Sampling

Teacher(s)

Guisset Séverine; Ritter Christian;

Language

French

Prerequisites

Concepts and tools equivalent to those taught in teaching unit

LSTAT2014

Eléments de probabilités et de statistique mathématique

Main themes

Topics to be treated - General framework of inference in finite population; population, sampling, statistics for the inference based on experimental data, linear homogenous estimation: elementary units, complex units. - Sampling with unequal probabilities: Hansen-Hurwitz and Horvitz-Thompson estimators, for the particular case of simple random sampling. - Estimators improvement through auxiliary information: ratio estimator, regression estimator - Sampling from complex units: stratified sampling, cluster sampling, two stages sampling. - Sampling from biological populations: basic issues in sampling, estimation of the population size.

Learning outcomes

At the end of this learning unit, the student is able to :
1	Objective (in terms of abilities and knowledge) This course aims at providing the student the basic knowledges on the sampling methods, with a particular, but not exclusive, emphasis on sampling from (finite) human populations. At the end of the course, the student should be able to correctly designing a simple survey and analysing the results.

Content

General framework of  inference in finite population :

• Techniques of random samplings and estimators properties.
• Simple random sampling
• Stratified random sampling
• Uneven probability sampling
• Cluster sampling
• Multi-level sampling

Estimation improvement by use of auxiliary information.

Teaching methods

8 x 2 hours of masterful presentations and 2 x 2 hours of practical exercices on computer.
This teaching is designed to adapt quickly to health developments (face-to-face, co-modal or distance teaching). Students are encouraged to regularly check their class schedule on ADE as well as the information available on Moodle.

Evaluation methods

Written exam in session and/or individual project assessed on the project report and its oral defense.

Other information

It is essential to have taken and successfully completed at least one course in inferential statistics.

Online resources

MOODLEUCL : lecture LSTAT2200.

Bibliography

Mouchart M. et J.-M. Rolin (1981), Enquêtes et Sondages, Série " Recyclage en Statistique ", Vol.5, , Louvain : U.C.L., Comité de Statistique.
Sharon Lohr (1999), Sampling : Design and Analysis, Duxbury Press Rao Poduri S.R.S. (2000), Sampling Methodologies with Applications, London : Chapman and Hall.

Teaching materials

• Transparents sur moodle
• Documents divers

Faculty or entity

> LSBA