Sampling (Population: Entire set of people or products in which you are…
Population: Entire set of people or products in which you are interested.
Census: Gathering information from the whole population
Sample: Smaller set taken from the population
Non-Probability Sampling: Nonrandom sampling that can lead to a biased sample.
Unknown External Validity
Convenience Sampling: Sample is chosen based only off of who is easy to reach.
Purposive Sampling: Certain kinds of people are chosen for a certain characteristic in a nonrandom way.
Self-Selected Sample: Participants volunteer themselves.
Quota Sampling: The researcher tried to get the sample as close to the representative population as possible without a sampling frame.
Snowball Sampling: Participants recruit other participants for a study.
Probability Sampling: Every member of the population has an equal and known chance of being selected for the sample.
Cluster Sampling: People in the population are already divided into natural groups. Clusters within a population are randomly selected and all people within that cluster are used.
Multistage Sampling: A random cluster is selected and then random people within that cluster are selected.
Stratified Random Sampling: Demographic categories are selected and then random individuals within those categories are selected, creating a sample that is proportional to the population.
Oversampling: One or more groups are purposely overrepresented because the base rate is low. This is statistically controlled for later.
Systematic Sampling: Every nth person is selected to participate.
Known Error of Estimation (Margin of Error)
Simple Random Sampling: People from the population are randomly selected.
Researcher has a known sampling frame (list of people forming the population from which the sample is taken).