Simple random sampling means every member of your population has an equal chance of being picked — like drawing names from a hat. Nobody is favoured, so the sample is fair and the results can reasonably represent the whole group. It is the most basic probability sampling method and the easiest to defend when your population is small and you have a list of everyone in it.
When to Use It
- You have a complete list of everyone in your population.
- The population is fairly uniform — no major subgroups you need to balance.
- You want a fair, unbiased sample that is easy to justify.
- The population is small enough to manage the random selection.
When Not to Use It
- You have no full list of the population — you cannot randomise what you cannot list.
- Important subgroups might be missed by chance — use stratified sampling instead.
- The population is huge and scattered, making a full list impractical.
How to Do It (Plainly)
- Get a complete numbered list of your population (the sampling frame).
- Decide your sample size (see sample size determination).
- Use a random method — a random number generator, or writing numbers and balloting — to pick that many.
- Those selected are your sample; everyone had an equal chance.
Nigerian Project Example
From a list of 300 final-year Accounting students, you number them 1–300, then use a random number generator to pick 169. Every student had the same chance of being chosen, so your sample fairly represents the class.
Undergraduate vs Postgraduate
Undergraduates often use simple random sampling because it is easy to explain and defend. Postgraduates dealing with diverse populations frequently move to stratified or multi-stage sampling to make sure key subgroups are properly represented.
Common Mistakes
- Calling convenience sampling "random" because it sounds better.
- Trying to randomise without a complete list of the population.
- Using it when subgroups are unequal and end up under-represented.
State your sampling method clearly in your methodology — see how to write Chapter Three and the full research methodology guide. Compare it with stratified sampling and systematic sampling. Project Lab can help you choose and justify the right technique.
Frequently Asked Questions
Is simple random sampling the same as convenience sampling?
No. Convenience sampling picks whoever is easy to reach, which introduces bias. Simple random sampling gives every member an equal chance through a genuine random method.
Do I need the full list of my population?
Yes. Without a complete list (a sampling frame), you cannot give everyone an equal chance, so it is not truly random. If you cannot get a list, consider a different technique.