#### What is Sampling?

Sampling is the process of collecting units (e.g., people) that represent a bigger population of interest. The accessible population is the portion of the population that the researcher can access and sample from, otherwise referred to as the study population. Finally, the group of people or objects that are selected from the accessible population is the sample. The number of cases in the accessible population is represented by an uppercase N, while the number of cases in the sample is represented by a lowercase n.

Cluster sampling involves two layers of sampling; the first layer selects clusters, or naturally occurring groups (e.g., yoga classes), and the second layer selects individuals from within those clusters (e.g., students of those yoga classes). Researchers can assess differences between classes as a whole (i.e., the cluster) or differences between individual students. Whatever major entity is being assessed in the results is referred to as the unit of analysis. For example, if a study compares student performance across different students, the unit of analysis is the student. If a study compares average student performance across different classes, the unit of analysis is the class. Analytic Sample: the sample at the time final outcomes are measured

Baseline Sample: the sample at the time of assignment to groups

Generalize: to make conclusions about a larger group based on a subset of that group

Population: overall group the research is interested in

Sample: a subset of the population of interest that is selected for the study

Sample Size: number of units in the sample, commonly referred to as n

Selection Bias: when the sample selected is not representative of the population

Statistical Power: the likelihood that a study will detect an effect (when there is an effect to be detected)