Briefly define and discuss random sampling error, non-sampling error, and the two major types of non-sampling error

What will be an ideal response?

Random sampling error occurs because the particular sample selected is an imperfect representation of the population of interest. Random sampling error is the variation between the true mean value for the population and the true mean value for the original sample.

Non-sampling errors can be attributed to sources other than sampling, and they may be random or nonrandom. They result from a variety of reasons, including errors in problem definition, approach, scales, questionnaire design, interviewing methods, and data preparation and analysis.

Non-response error arises when some of the respondents included in the sample do not respond. The primary causes of non-response are refusals and not-at-homes. Non-response will cause the net or resulting sample to be different in size or composition from the original sample. Non-response error is defined as the variation between the true mean value of the variable in the original sample and the true mean value in the net sample.

Response error arises when respondents give inaccurate answers or their answers are mis-recorded or mis-analyzed. Response error is defined as the variation between the true mean value of the variable in the net sample and the observed mean value obtained in the marketing research project.