1.3 Data Sampling Types

Cluster sampling is a sampling technique where the population is divided into groups (clusters), and a random sample of these clusters is selected. All individuals within the chosen clusters are then surveyed.

Convenience sampling is a non-probability sampling technique where samples are taken from a group that is easily accessible to the researcher.

Random sampling is a sampling technique where each member of the population has an equal chance of being selected, ensuring that the sample is representative of the population.

Systematic sampling is a method where samples are selected at regular intervals from a randomly ordered list of the population.

Stratified sampling is a technique where the population is divided into subgroups (strata) that share similar characteristics, and random samples are taken from each stratum.

A researcher surveys all students in randomly selected classrooms within a school.

A student surveys friends and family members for a project.

A lottery system where names are drawn randomly from a hat.

Selecting every 10th person from a list of registered voters.

Dividing a population of voters into age groups and randomly selecting individuals from each age group.