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What is stratified random sampling?
A sampling method that divides a population into subgroups (strata) and randomly samples from each subgroup.
What are strata in stratified random sampling?
Strata are the distinct subgroups within a population that share similar characteristics.
Why use stratified random sampling?
To ensure representation of all subgroups in the population and improve the precision of the overall sample estimate.
How do you determine the size of each stratum?
The size of each stratum is often based on its proportionate representation in the overall population.
What is the difference between proportionate and disproportionate stratified sampling?
Proportionate sampling samples each stratum in proportion to its size, while disproportionate sampling does not.
What is one advantage of stratified random sampling?
It reduces sampling variability and can lead to more reliable estimates.
What is one disadvantage of stratified random sampling?
It can be more complex and time-consuming to implement than simpler sampling methods.
In what fields is stratified random sampling commonly used?
It's commonly used in social sciences, market research, and health studies.
What is an example of a stratum?
Age, gender, income level, or education level can all serve as examples of strata.
How is stratified random sampling conducted?
Identify strata, determine sample size for each stratum, and then randomly select samples from each stratum.
