Simple random sampling
Simple random sampling gives every unit an equal and independent chance of selection. It is the benchmark design against which other methods are evaluated for bias and efficiency, and is free from systematic favouritism.
FrameworkSampling design
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Simple random sampling gives every unit in the population an equal, independent chance of selection, requires a complete list of that population, and serves as the benchmark design against which all other sampling methods are judged for bias and efficiency. Stratified sampling instead splits the population into known subgroups first, which can reach the same precision with a smaller total sample when those subgroups differ substantially.
Check yourself
A quality inspector numbers every component in a batch from 1 to 1,000 and uses a random number generator to select 50 numbers. She tests the selected components. What makes this simple random sampling, and which feature below is NOT part of its definition?