Total error in marketing research is the deviation between the true value and the observed value in the project. Numerous errors can affect the quality and credibility of the research findings. Two main types of errors have been identified: Random sampling errors and Non-random sampling errors. The first derives from how well the sample selected represent the population being studied while the latter represents all types of error that may occur from sources other than sampling.
Since non-sampling error is very broad it has been divided into response errors and non-response errors. While non-response errors are mainly cause by refusal to participate in a survey or not-at-home, response errors are generated by either the participant, or the researcher or the interviewer. Sampling error affect the total error however that effect is relatively small to the consequences of non-sampling error. Researcher should aim to design their research in a way to minimize the total error instead of a particular type of error in order to get the most accurate results.
In their book, -Marketing Research- Malhotra, Briks & Wills elaborated about sample sampling errors and non-sampling errors by describing them as follows.
“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 true mean value for the population and the true mean value for the original sample.” Therefore sampling error appears when the characteristic of a sample is representing the entire population being under research. For instance, if we are studying the average weight in Oman and we take a sample of ten thousand persons living in the Sultanate, their average weight will not be identical to the average weight of the entire population of the Sultanate of Oman (3.314 million). The variation between those two is what we call sampling error.
This type of mistake can be reduced by increasing the sample size and by developing an appropriate sampling plan.
Whereas, they added by explaining: “Non-sampling errors can be attributed to sources other than sampling and may be random or non-random. They result from a variety of reasons, including errors in problem definition, approach, scales, questionnaire design, interviewing methods, and data preparation and analysis. Non-sampling error consist of non-response errors and response errors.”
As also defined in Wikipedia, non-sampling error sums up all the errors that may occur in research except those related to sampling. Those types of errors are much harder to discover and measure compared to the sampling errors.
Different terms may be used to describe non-sampling errors, however they all mean the same. Unlike sampling errors, this category of error is practically impossible to abolish completely as they appear in different forms and the names used to label them are not consistent as mentioned in the glossary of the ministry of...