Survey and Sampling

lstat2200  2022-2023  Louvain-la-Neuve

Survey and Sampling
4.00 credits
15.0 h + 5.0 h
Concepts and tools equivalent to those taught in teaching unit
LSTAT2014Eléments 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.
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.
Tillé, Y. (2001). Théorie des sondages : échantillonnage et estimation en populations finies, (Cours et exercices avec solutions), Dunod, Paris.
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

Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Learning outcomes
Master [120] in Data Science : Statistic

Master [120] in Statistics: Biostatistics

Master [120] in Statistics: General

Approfondissement en statistique et sciences des données

Master [120] in Economics: General

Mineure en statistique et science des données

Master [120] in Data Science Engineering

Minor in Statistics, Actuarial Sciences and Data Sciences

Certificat d'université : Statistique et science des données (15/30 crédits)

Master [120] in Data Science: Information Technology