# 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 convenience 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.