Discover published sets by community

A sampling procedure where every member of the population has an equal chance of being selected. It's appropriate when you want an unbiased representation of the population.

A sampling method where you select members of a population at regular intervals. It's appropriate when you have a listed population and want a simpler alternative to random sampling.

This technique separates the population into subgroups (strata) and then randomly samples from each group. It's appropriate for ensuring representation from all subgroups within the population.

A sampling method where the population is divided into clusters, and a random sample of these clusters is then selected for study. It's suitable for large, geographically dispersed populations.

Involves choosing subjects who are easiest to access. It's appropriate when accessibility is a priority over representativeness, often used in exploratory research.

Sampling method where the population is segmented into mutually exclusive sub-groups, similar to stratified sampling, and researcher selects the subjects based on a fixed quota. It's appropriate when time or cost constraints prevent random sampling.

Participants are selected based on a specific purpose rather than randomly. It's appropriate when you are studying a specific characteristic or phenomenon within a population.

Where current study subjects recruit future subjects from among their acquaintances. It's appropriate for hard-to-reach or secretive populations.

A non-random sampling technique where the researcher uses their judgment to select participants. It's appropriate when a specific type of individual is needed for the study.

A sampling method where the probability of selecting a unit is proportional to its size. It's appropriate when studying populations with units of varying sizes.

A complex form of cluster sampling where multiple sampling techniques are used at different stages. It's appropriate for very large populations or studies with limited resources.

Relies on participants self-selecting to be part of the sample. It's appropriate when research constraints limit the ability to select a random sample.

Sampling methods that adapt as understanding of the population increases. It's appropriate for populations where the distribution of a characteristic is rare or clustered.

Involves taking samples in sequence until reaching a desired level of precision or certainty. It's appropriate for research where the outcome is uncertain or resources are limited.

A general category of sampling techniques that do not give all members of the population a chance to be selected. It's appropriate in qualitative research, exploratory research, or when random sampling is not possible.

A longitudinal study where data is collected from the same subjects repeatedly over a period of time. It's appropriate for studies aimed at detecting changes within a sample over time.

A type of snowball sampling particularly used in social science research. It's appropriate for hidden populations and combines snowball sampling with a mathematical model that compensates for non-random sampling.

A type of cluster sampling where the primary sampling unit is geographic areas. It's appropriate when the population is spread over a large geographic territory.

A variant of systematic sampling where samples are taken at specific time intervals. It's appropriate for continuous or repetitive processes.