Changes in technology and society strongly influence modern survey research. Survey Research - Statistical Analysis and Estimation course offered by Utrecht Summer School covers the essentials of modern survey analysis and estimation, and is organized by the Department of Methodology and Statistics (UU) in collaboration with Statistics Netherlands (CBS). Lectures, practical applications, and computer classes are alternated.
The course is intended for advanced students and professionals in such fields as social and behavioral research, marketing, business, health sciences, and official statistics. The course aims at researchers who intend to design and analyze their own survey, but also at researchers who analyze secondary data sets, such as the European Social Survey (ESS) or the International Social Survey Program (ISSP).
Central to the course is survey quality and the reduction of Total Survey Error (coverage, sampling, nonresponse, adjustment, measurement error, and processing error). Participants will be presented with tools for detection and adjustment of such errors. Analysis methods are introduced using both SPSS and R.
This course aims to provide participants with state of the art knowledge and application oriented skills for survey analysis and estimation. After the course, participants are ready to apply the learned towards their own data or archived data sets, and are able to take advanced training in complex survey statistics and adjustment.
You can apply until:
Always verify the dates on the programme website.
24 August - 28 August
1.5 ECTS credits.
This programme may require students to demonstrate proficiency in English.
Housing fee:€ 200.00
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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