Sampling and Estimation
This course gives you useful knowledge about planning and assessing different types of survey designs. You will learn to explain the advantages and disadvantages of standard sampling designs, how to choose appropriate sampling designs for different selection problems and how to choose suitable estimators depending on the problem and the access to auxiliary information. You will be able to carry out estimation and precision estimation on data from different sampling designs, with and without auxiliary information and to describe and use common estimation methods for non-response problems, including imputation and calibration. The course treats several different sampling methods and different estimation procedures are discussed.
The methods you will learn through the course are: simple random sampling, stratified sampling, sampling with varying inclusion probabilities (known as πps-sampling), cluster sampling, multistage sampling and systematic sampling. Within the course you will discuss how to choose between methods and designs and how to implement them. The course also discusses different estimation procedures, particularly when there are different types of auxiliary information in the frame.
You will also get insights about the literature and scientific publications on the field.
The course is given at day time, full time.
The course forms a part of the Master's Program in Statistics, but it can also be studied as a freestanding course.
Teaching Format
The teaching forms consist of lectures and exercises.
Course information
More information for registered students will be found in Athena.
Teacher fall 2025
Course coordinator
You will find Edgar's reception hours in the link above. If you want to visit Edgar outside of his reception hours, you are welcome to e-mail him for an appointment.
Assessment
Examination will be in the form of written and oral examination.
If you have questions about studying at the Department of Statistics, please contact our study- and career counselor.





