Sampling
The specific process or technique used by a researcher to select a sample from a broader population.
What is Sampling?
Sampling encompasses the methodological rules for inclusion. It is broadly divided into probability sampling (e.g., simple random, stratified), where every member of the population has a known, non-zero chance of selection, allowing for statistical generalization; and non-probability sampling (e.g., convenience, purposive), which relies on researcher judgment or availability, limiting statistical generalizability but often necessary for qualitative or exploratory work.
Why Sampling Matters
The sampling method determines the external validity of the study. It dictates whether the researcher can mathematically estimate the margin of error when projecting findings from the sample back to the population.
Example
Using a stratified random sampling technique to ensure that the sample of 500 university students includes an exact proportional representation of freshmen, sophomores, juniors, and seniors based on the university's overall enrollment data.
Common Mistakes
- Using convenience sampling (e.g., surveying people who happen to walk by) but subsequently using inferential statistics to claim the findings represent the whole population.
- Failing to transparently report the exact sampling methodology, making it impossible for readers to evaluate the risk of selection bias.