Review:
Stratified Sampling
overall review score: 4.5
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score is between 0 and 5
Stratified sampling is a method of sampling in which the population is divided into subgroups or strata, and samples are then randomly selected from each stratum to ensure representation of all groups.
Key Features
- Population divided into strata
- Random sampling within each stratum
- Ensures representation of all subgroups
Pros
- Ensures representation of all groups in the population
- Reduces sampling error compared to simple random sampling
- Useful for studying specific subgroups within a population
Cons
- Requires knowledge of the population and its characteristics to properly stratify