Exhibit 34.8,
on the left) accumulate across the entire sample and can lead to results that are not representative
of the population. These errors can arise from factors such as poorly worded questions that
inadvertently influence responses or issues with coverage, where certain segments of the target
population cannot be reached. Systematic errors are of greater concern as they introduce bias into
the final results. Unlike sampling inaccuracies, increasing the sample size does not reduce bias
resulting from systematic errors.
To minimize bias, the nature of the study needs to be carefully considered. For
example, in shopper trend studies, respondents should be selected in a way that neutralizes bias
arising from their proximity to shopping outlets, as shopping habits are heavily influenced by
store location.
Non-sampling error can be reduced by maintaining reliable survey frames, designing
and testing questionnaires carefully, providing thorough training to the data collection team
(interviewers, auditors), implementing monitoring and call-back procedures, and maintaining high
standards in measurement and data processing systems.