A population is an entire group with specified characteristics. The target group/population is the desired population subgroup to be studied, and therefore want research findings to generalise to. A target group is usually too large to study in its entirety, so sampling methods are used to choose a representative sample from the target group.
A representative sample is a subset of the target group with a similar distribution of relevant characteristics, in turn allowing us to generalise from the sample to the target group with some justification. An unrepresentative sample is one that does not reflect the distribution of characteristics of the target group, cannot be generalised to the target population, and is therefore biased.
There are a number of different sampling methods. Let's take a look at each briefly.
This method gives every member of the target group an equal chance of being selected for the sample (e.g. by assigning a number to each member, and then selecting from the pool at using a random number generator).
A systematic method is chosen for selecting from a target group, e.g. every fourth person in a list could be used in the sample. It differs from random sampling in that it does not give an equal chance of selection to each individual in the target group.
Here the sampler divides or 'stratifies' the target group into sections, each showing a key characteristic which should be present in the final sample. Then each of those sections is sampled individually. The sample thus created should contain members from each key characteristic in a proportion representative of the target population.
Participants who are both accessible and willing to take part are targeted, e.g. employees from a conveniently located employer near the laboratory could be selected for the sample group.
Here the sample consists of people who have volunteered to be in the study.
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