Simple random sampling
Simple random sampling is the ‘name in the hat’ method. We have a population and a list of all the members of the population, and then randomly select members of the population to be in our sample. Each member of the population has an equal chance of being selected for the sample.
Simple random sampling is where each member of a population has an equal, random chance of being sampled.
Advantages of simple random sampling
- It’s easy to understand.
- It can be easy to implement, if we can feasibly survey any random member of the population (e.g. they live in a small area).
- It’s unbiased, because every member of the population has an equal chance of being selected for the sample.
- It will usually give us a representative sample, because every member of the population has an equal chance of being selected for the sample.
Disadvantages of simple random sampling
- It can be difficult to implement, if we can’t feasibly survey any random member of the population (e.g. they live in a large area).
- It can be time-consuming and expensive to implement, especially if the population is large.
- It may not give us a representative sample, because we might by chance select a sample that is not representative of the population (e.g. we might accidentally select a sample that is all from one area, or all from one age group, etc.).
flashcards
| Question | Answer |
|---|---|
| Simple random sampling | Each member of a population has an equal, random chance of being sampled. It is the ‘name in the hat’ method where members are randomly selected from a list of the entire population. |
| What is an advantage of simple random sampling regarding understanding? | It is easy to understand. |
| What is an advantage of simple random sampling regarding implementation? | It can be easy to implement if we can feasibly survey any random member of the population (e.g. they live in a small area). |
| How does simple random sampling ensure the sample is unbiased? | Every member of the population has an equal chance of being selected for the sample. |
| Why does simple random sampling usually give a representative sample? | Because every member of the population has an equal chance of being selected for the sample. |
| What is a disadvantage of simple random sampling regarding a large population? | It can be time-consuming and expensive to implement, especially if the population is large. |
| When can simple random sampling be difficult to implement? | If we can’t feasibly survey any random member of the population (e.g. they live in a large area). |
| Why might simple random sampling not give a representative sample? | Because we might by chance select a sample that is not representative of the population (e.g. we might accidentally select a sample that is all from one area, or all from one age group). |