Sampling Methods Review

A convenience sample is a type of non-probability sampling where the sample is taken from a group that is easily accessible to the researcher.

A simple random sample is a sampling method where every individual has an equal chance of being selected, often achieved using random number generators.

A stratified random sample is a sampling method where the population is divided into subgroups (strata) and random samples are taken from each stratum.

A cluster sample is a sampling method where the population is divided into clusters (often geographically), and entire clusters are randomly selected.

The population is the entire group of individuals or instances about whom we hope to learn.

Sampling bias occurs when certain members of the population are systematically more likely to be selected than others, leading to an unrepresentative sample.

Qualitative data describes characteristics or qualities, while quantitative data involves numerical measurements.

The purpose of random sampling is to ensure that every individual has an equal chance of being selected, which helps to eliminate bias.

A survey is a method of collecting data by asking questions to a group of people to gather information about their opinions, behaviors, or characteristics.

A sample is a subset of individuals selected from a larger population, used to make inferences about the population.