[ 551STMESPVK14 ] KV Sampling Methods

(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
4 ECTS B2 - Bachelor's programme 2. year Statistics Helga Wagner 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)keine
Original study plan Bachelor's programme Statistics 2015W
Objectives Students learn to draw probabilty samples from existing populations. They can use information on the population to choose an adequate sampling design and estimation procedure. Furthermore, students acquire the ability to look in-depth at literature in sampling theory, particularly in the "missing data" literature.
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, small area estimation

nonresponse (data imputation, weighting adjustment), variance estimation by resampling

Criteria for evaluation Homework assignments and a final examination
Methods Lecture by instructor

discussion of the homework assignments by the students

working with sample data in R (or Excel)

Language German
Study material Quatember, A. (current version). 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.

Changing subject? No
Corresponding lecture (*)4MSSTKV: KV Stichprobenverfahren (4 ECTS)
On-site course
Maximum number of participants 40
Assignment procedure Assignment according to priority