Sampling

Snowball sampling is a non-probability sampling method in which existing participants help the researcher reach other people who fit the study criteria. Instead of beginning with a complete list of everyone in the population, the researcher begins with a small number of suitable contacts, asks them for referrals, and gradually builds the sample through those […]

Systematic sampling is a probability-based sampling method in which researchers select units from an ordered list at regular intervals after choosing a random starting point. Instead of drawing every case separately, the researcher decides on a sampling interval and then follows that interval through the sampling frame. The method is popular because it is easy

Cluster sampling is a probability-based sampling method in which researchers select groups first, rather than selecting every person, record, household, school, clinic, or observation directly from one long list. These groups are called clusters. Once clusters have been selected, the researcher collects data from all eligible units inside them or samples further within them. This

Purposive sampling is a non-probability sampling method in which researchers select people, cases, documents, events, sites, or records because they fit the purpose of the study. Instead of asking chance to decide who enters the sample, the researcher uses clear criteria to find units that can speak directly to the research question. This article explains

Convenience sampling is a non-probability sampling method in which people, cases, records, places, or observations are selected because they are easy for the researcher to access. Instead of drawing names from a complete list or using a chance-based procedure, the researcher works with the units that are available within a classroom, clinic, organisation, online group,

Stratified sampling is a probability-based sampling method in which a population is divided into meaningful subgroups before the sample is selected. These subgroups are called strata. Instead of drawing one sample from the whole population at once, the researcher draws a sample from each stratum, so that important groups are included in a planned way.

Random sampling is a probability-based way of selecting people, cases, records, classrooms, households, sites, or observations from a larger population. Instead of choosing the units that are easiest to reach or most familiar to the researcher, the selection is guided by chance. This gives each eligible unit a known chance of entering the study and

Sampling is the process of selecting a smaller group of people, cases, records, observations, or units from a larger population so that the researcher can study that group in a careful and manageable way. Instead of trying to collect data from everyone or everything that could possibly belong to a study, sampling gives the researcher

Sampling methods are the procedures researchers use to choose a smaller group from a larger population. In a well-planned study, sampling is not an afterthought. It decides who enters the study, whose experiences or measurements are represented, and how far the findings can reasonably travel beyond the people who were actually observed. This article explains