The objectives of this course are to provide participants with fundamental knowledge in sampling design procedure for surveys, particularly in sampling design for household surveys with specific case studies from previous and ongoing large-scale surveys in Vietnam (e.g. Living Standard Survey, National Health Survey, Household Living Survey). The content included in the course aims to help participants gain insight into the following topics:
- Basic knowledge in sampling design and sampling error, impact of sampling design on surveys’ outcomes.
- Identify requirements from information user and policy makers on the collected indicator’s reliability, from which specify appropriate sampling size and sampling design methods.
- Identify methods to improve quality of stratified sample design by using information on sampling errors, impact of sampling design, and survey costs.
- Understand the significance of standardization of survey documents on sampling errors, serving the sampling design process in future surveys.
- Understand calculation methods for sampling weight (weight design, modification for unanswered cases and out-of survey scope) for surveys with stratified sample design.
- Understand design methods of panel data survey and application of this method in the process of measuring progress of studied indicators. This method will help reduce sampling errors and thus decrease the sample size needed to measure indicator changes over time.
The course is open to all people who possess basic statistics knowledge and who are working with survey data sets. The course is relevant for graduate students and researchers from universities, research institutes, and ministries.
Survey Sampling: Leslie Kish. Professor of Sociology. Program Director, Survey Research Center, Institute for Social Research, The University of Michigan.
- Basic statistics
- Basic mathematics
Content of the course
The course will last for 4 days with the content as follows:
- Sampling – Science or Art?
- Sampling error and Non-sampling error
- Basic knowledge about sample
- Multi-stage sampling method
- Estimation from multi-stage sampling method
- Maximization multi-stage sampling design
- Sampling design recommendation