Which type of sampling involves dividing the population into subgroups and selecting randomly from those?

Stratified sampling is a method that involves dividing the population into subgroups, known as strata, that share common characteristics such as age, gender, socioeconomic status, or other relevant factors. Once the population is divided into these distinct subgroups, researchers then randomly select samples from each stratum. This approach ensures that the sample accurately reflects the diversity of the entire population, as it allows for proportional representation of different groups.

By employing stratified sampling, researchers can obtain more precise data and draw more valid conclusions that can be generalized to the broader population. This technique is particularly beneficial when certain subgroups are underrepresented or have unique characteristics that may influence the research outcomes.