# Sampling and Population in Research

# Sampling

Sampling and population are two important and often confused subjects in research. They can be defined as;

**Population:** Theoretically specified group of studied elements or the large group results are generalized to

**Sample:** Study participants, usually a smaller group or a subset of the population

**Sampling:** process of selective study participants

There are two types of sampling, probability and it’s opposite. Within there these general types, there are many different examples and kinds. A few of them are listed below.

## Probability Sampling

- Every member of the population has a known & equal chance of being selected for the study
- Random selection is a key element

**Simple Random Sampling:**Each member of population is assigned a number, then random drawing of numbers is done.**Systematic Random Sampling:**Every kB element is selected (i.e. every 4th name is chosen)**Stratified Random Sampling:**- Group of participants are in layers / levels
- Break into groups, then randomly select from the groups

## Non-Probability Sampling

- Not random
- Unequal chance of selection

Types of non-probability sampling methods include:

**Snowball Sampling**- Participants refer others to the study
- Works well with hidden populations

**Convenience or Available Participants**- Just choosing participants because the people are available
- Often if a survey in the middle of the pub

**Quota**- The non-random parallel to stratified sampling
- Characteristic qualifies for study (i.e. demographic, age…etc)

**Purposive Sampling**- Criteria or diagnostic category qualifies for participation (not random)
- For example, finding information on people who have been molested and their cases have been brought to court