Cologne, Germany

Survey Sampling and Weighting

when 5 August 2024 - 9 August 2024
language English
duration 1 week
credits 4 EC
fee EUR 550

This practical course will cover the process of probability sampling and weighting for (social science) survey data. This includes a) sampling techniques, b) methods of weighting survey data including design weighting, nonresponse weighting, and adjustment weighting, and c) methods of parameter estimation for complex sample survey data. Please note that the course will only provide a short excursus to non-probability sampling. The emphasis of the course is more applied than theoretical, but you are expected to be comfortable with statistics and to have some experience with survey data analysis. For each topic, you will do exercises in Stata or R (based on your preference) that apply the techniques learned in the lectures. Prior knowledge in how to use Stata or R for survey data analysis is needed.

Course leader

Simon K├╝hne is Professor of Applied Social Data Science at the Faculty of Sociology at Bielefeld University, Germany. His research focus is on survey methodology, computational social science, and social inequality.

Target group

You will find the course useful if:
- you have experience conducting surveys and/or analyzing survey data but have no experience with survey sampling and weighting,
- you are planning your own survey data collection and need to sample and/or weight the data.

- Introductory course in statistics. No prior knowledge of sampling theory is assumed.
- Prior knowledge in Stata or R is required for this course.
- Basic understanding in survey methodology and how to handle survey data.

Course aim

By the end of the course, you will:
- know about the most commonly used sample designs including stratified sampling, cluster sampling, and multi-stage sampling,
- know how to create design weights, nonresponse weights, and apply adjustment weighting techniques,
- know how the sample design can affect data analysis and how to incorporate complex survey designs and survey weights into parameter estimation.

Credits info

4 EC
- Certificate of attendance issued upon completion.

Optional bookings:
The University of Mannheim acknowledges the workload for regular attendance, satisfactory work on daily assignments and for submitting a paper of 5000 words to the lecturer(s) by 15 October at the latest with 4 ECTS (70 EUR administration fee).

Fee info

EUR 550: Student/PhD student rate.
EUR 825: Academic/non-profit rate.
The rates include the tuition fee, course materials, the academic program, and coffee/tea breaks.


Scholarships are available from the European Survey Research Association (ESRA), see more information on our website