Simple Random Sample (SRS)
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Definition:
Every member of the population has an equal probability of being selected.- Example: Randomly drawing names from a hat.
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Key Features:
- No subgroups (strata) are defined.
- Requires a complete sampling frame (list of all population members).
- Minimal prior knowledge of population structure needed.
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Advantages:
- Simple to implement.
- Unbiased if the population is homogeneous.
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Disadvantages:
- May underrepresent small subgroups.
- Less precise if the population has significant variability.
Key Differences Vs. Stratified Sampling
| Feature | SRS | Stratified Sampling | |
|---|---|---|---|
| Subgroups | Ignores subgroups | Explicitly defines strata | |
| Precision | Lower for heterogeneous populations | Higher due to reduced variability | |
| Implementation | Simpler | More complex | |
| Use Case | Homogeneous populations | Populations with distinct subgroups | |
When to Use
- SRS: Best for small, homogeneous populations or when no prior subgroup information exists.
- Stratified: Ideal for populations with distinct subgroups needing precise representation (e.g., clinical trials, demographic surveys).