Survey and Sampling

lstat2200  2020-2021  Louvain-la-Neuve

Survey and Sampling
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
4 credits
15.0 h + 5.0 h
Kestemont Marie-Paule;
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.

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

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

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

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Written examination in session : 14 points on 20.
Individual project delivered for the beginning of the first session : 6 points on 20.
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
Faculty or entity

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

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

Master [120] in Economics: General

Mineure en statistique et science des données

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

Minor in Statistics, Actuarial Sciences and Data Sciences

Master [120] in Data Science Engineering

Master [120] in Data Science: Information Technology

Approfondissement en statistique et sciences des données

Master [120] in Statistic: General