Sample (statistics)

A sample is a subset of a population selected for observation, measurement, or analysis. Its data are used to describe the sample or estimate characteristics of the population.

Statistical population: The complete set of units or outcomes about which a statistical investigation seeks information. A sample is defined as a subset of this target set.
Sampling (statistics): The process of selecting units from a population to obtain data for statistical analysis. Sampling is the procedure that produces a sample.
Census: A study that collects data from every unit in a defined population. Unlike a sample, a census aims to observe the entire target population.
Stratified sampling: A probability sampling method that divides a population into strata and samples within each stratum. It ensures representation of specified subgroups in the sample.
Sampling unit: The individual element or group selected at a stage of a sampling design. Sampling units specify what is selected to form this sample.
Simple random sample: A sample selected so every possible sample of its fixed size has an equal chance of selection. This design gives a clear baseline for reasoning from a sample.
Convenience sampling: A nonprobability sampling method that selects units because they are easy to access. Convenient selection can make a sample systematically unlike its population.
Cluster sampling: A sampling method that selects groups of population units, then observes units within selected groups. It can reduce field costs when population members are geographically dispersed.
Sampling frame: A list or operational representation of units from which a sample can be selected. The frame determines which population members can enter the sample.
Sampling distribution: The probability distribution of a statistic across repeated samples drawn under the same design. It describes how estimates from samples vary across repeated selections.

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