Sampling
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.
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