Probability sampling, Involves random selection, allowing you to make strong statistical inferences about the whole group., Non-probability sampling, Involves non-random selection based on convenience or other criteria, allowing you to easily collect data., Simple Random sampling, Every member of the population has an equal chance of being selected., Systematic sampling, Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals., Cluster sampling, Involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups., Convenience sampling, Simply includes the individuals who happen to be most accessible to the researcher., Purposive sampling, Involves the researcher using their expertise to select a sample that is most useful to the purposes of the research., Snowball sampling, Can be used to recruit participants via other participants., Stratified sampling, Divide the population into subgroups (called strata) based on the relevant characteristic, Quota sampling, Relies on the non-random selection of a predetermined number or proportion of units.
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Sampling Techniques Match-Up
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