Which sampling method divides the population into subgroups and weights them based on national demographic characteristics?

Prepare for the UEL Clinical Psychology Screening Test. Study with a blend of insightful flashcards, incisively crafted questions, and reliable hints and explanations to excel in your exam!

Multiple Choice

Which sampling method divides the population into subgroups and weights them based on national demographic characteristics?

Explanation:
Stratified sampling divides the population into subgroups that share key characteristics (like age, gender, or region) and then samples from each subgroup. The “weights based on national demographic characteristics” part means adjusting the final results so the overall picture matches the country’s actual demographic makeup, either by sampling in proportion to each subgroup’s share or by applying weights after data collection. This approach helps ensure that each subgroup is represented appropriately and that the overall estimates reflect the national population. This differs from systematic random sampling, which simply picks every nth person from a list and doesn’t inherently ensure representation across demographics; purportive sampling aims for particular cases based on judgment rather than representativeness; and snowball sampling relies on participants to recruit others, which can bias the sample and is not designed to mirror national demographics.

Stratified sampling divides the population into subgroups that share key characteristics (like age, gender, or region) and then samples from each subgroup. The “weights based on national demographic characteristics” part means adjusting the final results so the overall picture matches the country’s actual demographic makeup, either by sampling in proportion to each subgroup’s share or by applying weights after data collection. This approach helps ensure that each subgroup is represented appropriately and that the overall estimates reflect the national population.

This differs from systematic random sampling, which simply picks every nth person from a list and doesn’t inherently ensure representation across demographics; purportive sampling aims for particular cases based on judgment rather than representativeness; and snowball sampling relies on participants to recruit others, which can bias the sample and is not designed to mirror national demographics.

Subscribe

Get the latest from Examzify

You can unsubscribe at any time. Read our privacy policy