Small sample sizes are when you're testing something using only a few people or things instead of a lot.
Imagine you’re trying to figure out if your favorite cereal is better than another one. If you ask just one friend what they think, that’s like having a small sample size, it might not be enough to know for sure what everyone thinks. But if you ask a whole class, that's more people and probably gives you a better idea.
Why Small Sample Sizes Can Be Trickier
Sometimes, when you have only a few things to look at, weird stuff can happen. Like if you flip a coin 5 times and it lands heads every time, you might think the coin is unfair! But really, with just a small sample size, that’s not unusual.
But if you flipped the coin 100 times and still got mostly heads, then you’d probably start to believe something was up!
So, small sample sizes can make it harder to see what's really going on, kind of like trying to guess a puzzle with only a few pieces.
Examples
- A poll asks ten people about their favorite ice cream flavor and says chocolate is the most popular.
Ask a question
See also
- What are nonparametric and semiparametric models?
- How Does The Problem of Multiple Comparisons | NEJM Evidence Work?
- What is identifiability?
- What is variance?
- What are statistical populations?