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Double Sampling Definition

Data is collected through an inexpensive sampling technique for a sample larger than the final desired sample size. A sub sample of this group is then selected and sampled - usually with a more expensive technique.

Double sampling is an inexpensive two-stage sampling technique used to enhance the accuracy and efficiency of data collection. In this method, a smaller preliminary sample, called the first stage, is collected from a larger population. Then, a final sample, called the second stage, is selected from the preliminary sample. This method combines the benefits of random sampling and stratified sampling, It improves representation and is cost-effective. Double sampling addresses the challenges of obtaining accurate information from large and diverse consumer populations. Its two-stage process allows for more targeted sampling, reducing bias and increasing the likelihood of capturing meaningful trends and patterns.

Who relies on double sampling?

Researchers and businesses use double sampling when dealing with large and diverse consumer populations in which obtaining a truly random sample is challenging. Researchers find this method to be valuable for mitigating bias, reducing costs and collecting more accurate insights for informed decision making.

Why should I care about double sampling?

Double sampling improves sample quality and saves resources. This knowledge empowers marketing professionals to assess research methodologies, which makes certain that the data collected is accurate and reliable.