Probability vs. Non-Probability Sampling

Also known as: Probability Sampling, Random Sampling, Non-probability Sampling

Fundamental methodological distinction: probability sampling guarantees each unit has a known selection probability; non-probability does not.

The distinction between Probability and Non-Probability Sampling is fundamental in research methodology:

Probability Sampling: each member of the population has a known, non-zero probability of being selected. Allows making statistically valid inferences about the total population with calculable margin of error. Examples: simple random sampling, stratified, systematic, and cluster sampling.

Non-Probability Sampling: selection is not random and does not allow calculating a formal statistical margin of error. Examples: convenience sampling, snowball sampling, quota sampling. Most current online studies are technically non-probability, although with quotas and weighting, representativeness is approximated.

Understanding this distinction is critical for correctly interpreting the statistical uncertainty of research results.