What is a common consequence of nonsampling error?

Inaccurate data collection is a common consequence of nonsampling error because nonsampling errors arise from various factors unrelated to the actual sampling process itself. These could include mistakes in data entry, survey design flaws, response bias, misinterpretation of questions by respondents, or issues during the data collection process. Such inaccuracies can significantly affect the quality of the data gathered, leading to unreliable results and conclusions.

When data collection is flawed, the insights derived from the research are called into question, and this undermines the validity of any analyses or decisions based on that data. Thus, inaccurate data collection directly highlights the impact of nonsampling errors on research outcomes.