Stratified Random Sampling
Stratified random sampling divides the population into distinct strata (sections or segments) to ensure adequate representation before selecting a random sample from each. This method improves the accuracy and representativeness of the sample.
Use this method when you want to ensure that specific subgroups within a population are adequately represented in the sample.
Solves: Underrepresentation of key subgroups in a simple random sample; Inaccurate conclusions due to biased sampling.
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Step 1: Identify the relevant strata (subgroups) within the population. (10 min)
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Step 2: Determine the proportion of each stratum in the overall population. (10 min)
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Step 3: Select a random sample from each stratum, proportional to its representation in the population. (20 min)
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Step 4: Analyze the combined sample. (20 min)
- Ensure strata are mutually exclusive and collectively exhaustive.
- Accurately determine the proportion of each stratum in the population.
- Use disproportionate stratified sampling to oversample smaller strata.
- Combine with cluster sampling for large, geographically dispersed populations.