Abstract
Social scientists are increasingly using surveys to collect data on behaviors, knowledge, perceptions, attitudes, and opinions from various population of interest. Most of the time, researchers are aware of survey limits to provide population estimates due to sampling error; however, social researchers are less aware of survey limits due to nonsampling errors. This chapter discusses the most defining characteristics of sampling and nonsampling errors in surveys. In particular, the chapter uses the Total Survey Error (TSE) approach as a way of helping social scientists to think comprehensively about the impact of different sources of error on survey estimates. The TSE is a valuable survey methodology theoretical framework which conceives the concept of survey error as a function of four factors: sampling error, coverage error, nonresponse error, and measurement error. This chapter emphasizes the importance of thinking inclusively about survey errors and data quality, with the ultimate purpose of minimizing the impact of error sources on survey estimates.
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