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There are 8 main types of sampling in statistics:

Simple Random Sample: Every possible sample in a population has an equal probability of being selected.
Census: Entire population is used in study (so it's really not a sample)
Stratified Random Sample: A sample in which a sample is taken from each of two separated groups (called strata), for example men and women. This is done as a "block", in case men and women will have different responses in the tested variable.
Systematic Random Sample: The same as a Stratified Random Sample, except the strata are divided for convenience only.
Judgement Sample: Sampled group is selected based on "judgement" (expert authority is sampled)
Convenience Sample: An example is in which a person wants to predict election results by simply surveying everyone on his street. Biased, usually, for obvious reasons.
Multistage Sample: A sample is divided into stages for easier sampling. Example: to predict election results, a surveyor selects 5 random states in the US, from which 5 random counties are selected, from which 5 random cities are selected, etc.
Voluntary Response Sample: A sample in which the sampled group volunteers for the study. Usually heavily biased, for obvious reasons. Those who respond are the ones who happen to feel most strongly about an issue.

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