# Statistics - Sample Types

A study needs participants and there are different ways of gathering them.

Some methods are better than others, but they might be more difficult.

## Different Types of Sampling Methods

### Random Sampling

A random sample is where every member of the population has an **equal chance** to be chosen.

Random sampling is the best. But, it can be difficult, or impossible, to make sure that it is completely random.

**Note:** Every other sampling method is compared to how close it is to a random sample - the closer, the better.

### Convenience Sampling

A convience sample is where the participants that are the easiest to reach are chosen.

**Note:** Convenience sampling is the easiest to do.

In many cases this sample will not be **similar** enough to the population, and the conclusions can potentially be useless.

### Systematic Sampling

A systematic sample is where the participants are chosen by some regular system.

For example:

- The first 30 people in a queue
- Every third on a list
- The first 10 and the last 10

### Stratified Sampling

A stratified sample is where the population is split into smaller groups called 'strata'.

The 'strata' can, for example, be based on demographics, like:

- Different age groups
- Professions

Stratification of a sample is the first step. Another sampling method (like random sampling) is used for the second step of choosing participants from all of the smaller groups (strata).

### Clustered Sampling

A clustered sample is where the population is split into smaller groups called 'clusters'.

The clusters are usually natural, like different cities in a country.

The clusters are chosen randomly for the sample.

All members of the clusters can participate in the sample, or members can be chosen randomly from the clusters in a third step.