Description: Non-sampling error refers to those errors that can arise in the data collection process that are not related to the sampling itself. These errors can be caused by various factors, such as measurement errors, response biases, problems in question formulation, or even incorrect interpretation of instructions by respondents. Unlike sampling errors, which are inherent to the process of selecting a representative sample from a population, non-sampling errors can occur at any stage of the research process. Identifying and minimizing these errors is crucial to ensure the validity and reliability of the results obtained in statistical studies. Therefore, it is essential for researchers to implement appropriate survey design techniques and training for interviewers to reduce the incidence of these errors. In summary, non-sampling error is a critical aspect of applied statistics, as it can significantly affect the quality of the data and, consequently, the conclusions drawn from it.
