Which type of error is attributable to mistakes made in the selection process or sample size determination?

The focus of the question is on errors that arise specifically from issues in selecting a sample or determining its size, which characterizes sampling error. Sampling error occurs when the sample chosen does not accurately represent the entire population. This can happen due to chance variations or an inadequate sample size that does not capture the diversity of the population.

Sampling error is significant in research because it affects the reliability of the results; a small or poorly chosen sample can lead to conclusions that differ from those that would be drawn by examining the whole population. Recognizing this type of error is essential for researchers, as it highlights the importance of appropriate sample selection and sufficient sample size to achieve valid and reliable data.

In contrast, nonsampling errors arise from other factors such as data collection or processing mistakes, which are not directly related to the sampling method. Quota sampling error is a specific type of nonsampling error related to the method of quota sampling, where specific characteristics of the population are required in the sample but may not accurately reflect the population proportions. Measurement error involves inaccuracies in how data is collected or measured, such as flawed survey questions or respondent misunderstanding, which again is separate from issues related to sample selection.