Research Methodology
Simple Random Sampling
A subset of a statistical population in which each member of the subset has an equal probability of being chosen.
What is Simple Random Sampling?
Simple random sampling requires a complete sampling frame of the target population. Subjects are selected entirely by chance, often using random number generators, ensuring that every possible sample of a given size is equally likely.
Why Simple Random Sampling Matters
It serves as the baseline method against which other sampling techniques are evaluated and provides the most straightforward path to unbiased population estimates.
Example
A university registrar assigns a random number to every currently enrolled student and uses a computer program to select 500 students to receive a campus climate survey.
Common Mistakes
- Thinking haphazard selection (like picking the first 10 people you see) is simple random sampling.
- Failing to account for an incomplete sampling frame (e.g., missing unregistered voters).