Cluster sampling: Is when the researcher chooses groups of clusters. After choosing the cluster the researcher then selects individual subjects further by simple random or systematic random sampling. An example is a geographical cluster.
If a researcher wanted to see the academic performance of high school students in Florida. He can divide the population of Florida into different clusters (cities).
From these clusters the researcher can select subjects from the clusters through simple random sampling.
Convenience Sampling: Convenience sampling is used with people who are easy to reach.
An example of this would be a researcher would do polls at a local shopping mall.
Systematic Sampling: Systematic sampling is when you start at a selected point randomly and from then on from a fixed periodic selection.
An example of this would be: Taking a sample of a population. If you wanted to select 1,000 people from 500,000 then using this approach you would select a point randomly and then choose the participants at a fixed periodical point such as every 50th person.
Stratified Sampling: Is a type of sampling method that the researcher divides the set population into different groups call "strata". Then the sample is drawn from each group.An example would be dividing a high school into different groups based on grade: freshman, junior, sophomore and senior.
Then taking a random sample from each group.
Simple Random Sampling: Is when each member of the population has an equal chance at being chosen. An example of this would be putting names into a hat and picking out of the hat randomly. Each person has an equal chance at being picked.
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