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

1. Simple Random Sampling: Each member of population is assigned a number, then random drawing of numbers is done.
2. Systematic Random Sampling: Every kB element is selected (i.e. every 4th name is chosen)
3. 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