What is Sampling?
Sampling is the selection of a set of elements from a target population or product lot. Sampling is frequently used because gathering data on every member of a target population or every product produced by a company is often impossible, impractical, or too costly to collect. Sampling lets you draw conclusions or make inferences about the population or product lot from which the sample is drawn (Figure 1).
Avoiding Sampling Errors
When used in conjunction with randomization, samples provide virtually identical characteristics relative to those of the population or product grouping from which the sample was drawn.
Beware, however, of three categories of sampling error:
- Bias (lack of accuracy)
- Dispersion (lack of precision)
- Non-reproducibility (lack of consistency)
These sampling errors are easily accounted for by knowledgeable practitioners.
How to Determine Minimal Sampling Sizes
Determinations of sample sizes for specific situations are readily obtained through the selection and application of the appropriate mathematical equation. All that is needed to determine the minimum sample size is to specify:
- If the data are continuous (variable) or discrete (attribute)
- If the population is finite or infinite
- What confidence level is desired/specified
- The magnitude of the maximum allowable error (due to bias, dispersion, and/or non-reproducibility)
- The likelihood of occurrence of a specific event
Adapted from Quality Essentials: A Reference Guide from A to Z, ASQ Quality Press.