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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, stratified random sampling, random cluster sampling and systematic 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.
The second type of probability sampling is stratified random sampling. 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.
Another method is random cluster sampling, which 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.
The final method of probability sampling, systematic sampling, is when the researcher selects every nth person to be observed; for example, every 3rd person. This provides an equal chance of selection for all participants.
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