Master's Programme in Mathematics and Statistics is responsible for the course.
The course belongs to the Statistics and Social statistics module.
The course is available to students from other degree programmes.
- Sample survey, register survey, data integration
- Sampling techniques
- Use of auxiliary data in sampling and estimation
- Estimators for finite population parameters (HT, GREG, calibration)
Ability to apply selected methods in practice
Recommended time/stage of studies for completion: 1. or 2. year
Term/teaching period when the course will be offered: varying
Course gives an overview on sampling methods and estimation under different sampling designs and the use of the methods in empirical research and statistics production. Methods include simple random sampling, systematic sampling, Bernoulli sampling, Poisson sampling, PPS sampling, stratified sampling and multi-stage sampling and the estimation of finite population parameters under the various sampling designs, including HT estimation, GREG estimation and calibration as well as variance estimation. Special emphasis is in methods to incorporate auxiliary information into sampling design and estimation design. Empirical examples and case studies are given.
Lehtonen R. and Pahkinen E. (2004) Practical Methods for Design and Analysis of Complex Surveys. 2nd Edition. Wiley.
Lectures and exercise classes
Exam and written assignment, Course will be graded with grades 1-5
Exam and written assignment