How does stratified random sampling differ from simple random sampling?
- Stratified random sampling always involves larger sample sizes than simple random sampling
- Stratified random sampling involves dividing the population into subgroups and selecting individuals from each subgroup
- Stratified random sampling is the same as simple random sampling
- Stratified random sampling only selects individuals from a single subgroup
Stratified random sampling differs from simple random sampling in that it first divides the population into non-overlapping groups, or strata, based on specific characteristics, and then selects a simple random sample from each stratum. This can ensure that each subgroup is adequately represented in the sample, which can increase the precision of estimates.
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