Entry requirements

Probability theory MN1, Inference theory MN1.

Probability theory MN2 and Inference theory NV2

are recommended.

Aims

The course provides thorough knowledge about inference from probability samples from finite populations, and how to design sample surveys in a cost efficient way. Moreover, it provides basic knowledge about statistical quality control.

Content

Simple random sampling, systematic sampling, cluster sampling (one- and two-stage), pps-sampling, and network sampling. Stratification. Optimisation of sample designs, i.a. for for repeated surveys. Error sources, notably non-response and measurements. Sample inspection by attiributes and variables, and chart procedures for production control. Practical examples.

Instruction

Lectures, problem solving sessions.

Assessment

Written and, possibly, supplementary oral

examination at the end of the course. In addition

assignments during the course.