Stratified sampling is a human-made statistical procedure for selecting a representative subset from a population. Its parameters are: (1) a population partitioned into mutually exclusive and collectively exhaustive strata based on a known characteristic; (2) an independent sampling mechanism applied within each stratum (typically random); (3) an allocation rule determining sample size per stratum (proportional, optimal, or equal). It persists through survey methodology, statistical practice, and academic instruction. [formal: stratificatus | substrate: behavior | horizon: a moment | explicit: yes | epoch: 0.01]
Accepted ontology entry
stratified-sampling
Stratified sampling is a human-made statistical procedure for selecting a representative subset from a population. Its parameters are: (1) a population partitioned into mutually exclusive and collectively exhaustive strata based on a known…
Definition
Why it is in scope
A human-made statistical procedure — dividing a population into mutually exclusive, known subgroups (strata) and selecting samples from each to ensure representation across all. Built to produce more precise estimates than simple random sampling for heterogeneous populations.
Names and aliases
- stratified-samplingen · CANONICAL
Relations from this entry
- cmrw4cxyb0087ekzzy0aa1ehaINSTANCE_OF →
Stratified sampling IS a specific kind of random sampling: the population is divided into strata and then random samples are drawn from each stratum. A competent speaker would call it a kind of random sampling.
- cmrw05y3202wz2cei9lz7lrwkDEPENDS_ON →
Remove randomization and stratified sampling stops operating — it is fundamentally defined by random selection within strata. Without the random component it becomes stratified selection, a different method. Present-tense removal test (Law 8).
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Record identity
- Created
- Jul 22, 2026, 1:40 PM UTC
- Content hash
- 1be28b61056ba5055f316b0e3fbfb8c58e5a74dbd3f0c714e63fa46cf3b3ba5b