The two main types of samples depend on context, but in statistics and research, the two main types are probability samples and non-probability samples. Probability samples are samples where every member of the population has a known, non-zero chance of being selected, and selection is random, which allows for generalization to the population and statistical inference. Types of probability samples include simple random sample, where everyone has equal chance, stratified sample, where population is divided into groups and randomly sampled within each, cluster sample, where groups or clusters are randomly selected, and systematic sample, where every nth person is selected. Non-probability samples are samples where selection is not random and not every member has a known chance, often based on convenience or judgment, which limits generalizability but is easier and cheaper. Types include convenience sample, purposive or judgmental sample, quota sample, and snowball sample. In a broader medical context, two main types could be biological samples like blood, urine, tissue versus non-biological samples like survey samples. In quality control, two main types could be random samples versus representative samples. But in statistics, probability versus non-probability is the fundamental distinction.
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