4 credits
15.0 h + 5.0 h
Q2
Teacher(s)
Kestemont Marie-Paule;
Language
French
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.
Aims
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. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
Summary: Content and methods
- 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.
Other information
Basic references:
- Mouchart, M. and J.-M. Rolin (1981), Enquêtes et sondages, Série "Recyclage en Statistique, Vol.5, U.C.L. Louvain : Comité de statistique.
- Lohr, Sharon L. (1999), Sampling : Design and Analysis, Duxburry Press: Brooks/Cole Publishing Company.
- Rao Poduri, S.R.S. (2000), Sampling Methodologies with Applications, London: Chapman and Hall.
Faculty or entity
LSBA
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Data Science Engineering
Master [120] in Statistics: General
Master [120] in Economics: General
Master [120] in data Science: Statistic
Master [120] in data Science: Information technology
Minor in Statistics and data sciences
Additionnal module in Statistics and data science