Stratified sample

Definition

A stratified sample is a sampling method where the population is divided into homogeneous subgroups, or strata, and random samples are taken from each stratum. This ensures that each subgroup is properly represented in the overall sample.

5 Must Know Facts For Your Next Test

1. Stratified sampling helps to increase precision and representativeness of the sample by ensuring all relevant subgroups are included.
2. The strata must be mutually exclusive; no individual should belong to more than one stratum.
3. Each stratum should be internally homogeneous but heterogeneous with respect to other strata.
4. The size of each sample from the strata can be proportional (proportional allocation) or equal (equal allocation) depending on the study's requirements.
5. Stratified sampling is particularly useful when there are distinct subpopulations and researchers want to ensure representation from all groups.

Review Questions

• What is the primary advantage of using a stratified sample over a simple random sample?
• How do you determine the strata in a stratified sampling method?
• Explain the difference between proportional allocation and equal allocation in stratified sampling.

Related terms

Simple Random Sample: A sampling method where every member of the population has an equal chance of being selected.

Cluster Sampling: A sampling technique where the population is divided into clusters, and entire clusters are randomly selected for analysis.

Systematic Sampling: A sampling method in which elements are selected at regular intervals from an ordered list.