Probability sampling

Probability sampling is a sampling method where all the participants, knowingly, have an equal chance at being selected based on probability. When a larger population is involved in a research study, it is not time or cost-effective to observe everyone, so only a few are chosen. Probability sampling is used on the assumption that random selection would create an accurate representation of the whole target population.

There are four types of probability sampling:

Simple random sampling: Simple random sampling involves the researcher assigning each participant with a number, then using an automated, random number selector to decide which participants are chosen.
Stratified random sampling: Involves the researcher putting each participant into smaller sub-groups that represent everyone in the target population. The sub-groups will not noticeably overlap and everyone in each group has an equal chance at being selected.
Random cluster sampling: Involves selecting participants randomly via geographical location. For example, to research people’s views about the UK government, the researcher would take samples from various locations around the UK to gain a better oversight of the whole target population.
Systematic sampling: Involves the researcher selecting every nth person to be observed; for example, every third person. This provides an equal chance of selection for all participants.

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