Exhibit 34.1 Sample size is a commercial decision
that weighs the costs of a larger sample against the benefits of greater
accuracy.
“In God we trust. All others must bring data.” — W. Edwards Deming.
A sample is a subset of the population or universe
that is selected for the purpose of making conclusions or inferences about the entire
population. By studying the sample, marketers can estimate parameters of interest such as
brand awareness, penetration, brand equity, market share, sales, or distribution, while
reducing the time, effort, and cost involved in collecting data from the entire population.
This chapter provides an overview of various sampling methods and discusses
the statistical considerations as also the commercial trade-offs (refer to illustration in
Exhibit 34.1) for determining appropriate sample sizes in retail tracking
and quantitative research studies. It explores the commonly used sampling standards employed
by research firms to ensure reliable and representative results. It also delves into the
concept of sampling and non-sample errors, both of which can affect the accuracy of the data
collected.
By thoroughly examining sampling methods, statistical aspects, and potential
errors, this chapter provides marketers and researchers with valuable insights into optimizing
their sampling techniques and enhancing the accuracy of their data analysis.