This course gives an introductory overview of the design and implementation of surveys from the initial planning phase to the data preparation as a final step. Topics include survey mode assessment and selection, sampling frames and designs, nonresponse, questionnaire design, cognitive pretesting, assessing measurement errors and data editing. The course is taught from a Total Survey Error perspective weighing data quality at each step of the process against associated costs.

This class is mainly targeted at master and Ph.D. Students that plan on conducting their own surveys.

 

The course is taught on-side through lectures, group exercises as well as personal tutorial meetings that give participants the opportunity to discuss their own survey designs. Each day we will discuss a specific topic that each focuses on one or more aspects of survey design within the Total Survey Error framework.

 

First, the choice of the survey mode is discussed, and how different ways to sample respondents follow from that choice. On the second day, we focus on the issue of survey nonresponse - how to prevent, analyze, and correct for it. On the third and fourth day, the actual survey content is discussed - how to write survey questions, make sure that they measure what they are intended to measure, test them, and finally, how to assess whether survey data are of good quality. On the final day, we focus on data coding and maximizing quality. We conclude with an overview perspective of all survey errors and their interaction with survey costs.

 

The course will be applicable to surveys of individuals, households, and organizations in different survey modes: mail, face-to-face, web, and paper-and-pencil surveys.

 

 

For additional details on the course and a day-to-day schedule, please download the full-length syllabus.