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| Detailed information |
| Pre-requisites |
(*)keine
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| Original study plan |
Bachelor's programme Statistics 2014W |
| Objectives |
Students will learn to draw probabilty samples out of existing populations on their own. They will learn to use information on the population to be able to choose an adequate sampling design and estimation procedure. Furthermore, students will possess the ability to look in-depth at literature in sampling theory, particularly in the "missing data" literature.
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| Subject |
Representativeness of samples, simple random sampling, stratified random sampling, cluster sampling, two-stage random sampling, non-random sampling (quota sampling), Horvitz-Thompson estimator, ratio and regression estimation, the problem with nonresponse, basics of bootstrapping
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| Criteria for evaluation |
Homework assignments and a final examination
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| Methods |
- Lecture by instructor
- discussion of the homework assignments by the students
- independent work with sample data
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| Language |
German |
| Study material |
- Quatember, A. (2014). Datenqualität in Stichprobenerhebungen - Stichprobenverfahren. Springer, Heidelberg.
Supplementary material:
- Lohr, S. (2010). Sampling: Design and Analysis. 2nd edition, Brooks/Cole, Boston.
- Särndal, C.-E., Swensson, B. and Wretman, J. (1992). Model Assisted Survey Sampling. Springer, New York.
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| Changing subject? |
No |
| Further information |
This course will only be offered during the Summer Semester.
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| Earlier variants |
They also cover the requirements of the curriculum (from - to)
4MSSTKV: KV Sampling Methods (2002W-2014S)
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