Simple random sampling is the most basic method of random sampling. Having a random sample means that anyone in the population had an approximately equal probability of being selected for the sample. Think of it like picking names out of a hat. It works especially well with larger sample sizes, as the more names you draw from the hat, the likelier it is that the names you’ve drawn represent the demographics and opinions of all of the names in the hat.
You can watch the short excerpt of this video from Simple Learning Pro to get the gist of how simple random sampling works.
Here is a summary of some of the pros and cons of simple random sampling.
| Pros | Cons |
|---|---|
| Less biased since participants are chosen at random | Potential for sample selection bias |
| More simple | Can be difficult to gain access to data of larger population |
While simple random sampling is the most straightforward method of sampling, it is not always the most appropriate to the situation. Let’s learn about alternatives.
