Nonsampling errors

Definition

Nonsampling errors are errors that occur in data collection, recording, and processing that are not related to the act of sampling. These errors can arise from survey design flaws, respondent errors, or data handling mistakes.

5 Must Know Facts For Your Next Test

1. Nonsampling errors can occur at any stage of the data collection process, including during questionnaire design and respondent interaction.
2. Common sources of nonsampling error include measurement error, processing error, coverage error, and nonresponse error.
3. Unlike sampling errors, nonsampling errors do not decrease with an increase in sample size and can be present even in a census.
4. Mitigating nonsampling errors often requires careful planning and execution of surveys, as well as rigorous validation and quality control measures.
5. Nonsampling errors can introduce bias into the study results if not properly addressed.

Review Questions

• What are some common sources of nonsampling errors?
• How do nonsampling errors differ from sampling errors?
• Why is it important to address nonsampling errors in statistical studies?

Related terms

Sampling Error: The difference between a sample statistic and its corresponding population parameter due to the randomness inherent in sampling.

Bias: A systematic error that leads to results or estimates that deviate from the true values.

Nonresponse Error: A type of nonsampling error that occurs when individuals selected for the sample do not respond or cannot be contacted.