Final answer:
A stratified random sample involves dividing the population into mutually exclusive groups and drawing random samples from each group. It ensures that each subgroup of the population is proportionally represented in the sample.
Step-by-step explanation:
In a stratified random sample, the population is divided into mutually exclusive groups (or strata) and random samples are drawn from each group. Stratified sampling is a method for selecting a random sample used to ensure that subgroups of the population are represented adequately.
To execute a stratified sampling method, you must first identify the different strata within the population. These could be categories like age groups, income levels, or any other divisions that are relevant to the research objective. Once the strata are determined, you apply simple random sampling to each stratum to select a proportionate number of individuals. This helps maintain the same ratio of the subgroups in the sample as they exist in the population, enhancing the validity and representativeness of the results.
For example, if education researchers wanted to survey high school students on their study habits, they would first stratify the student population by grade level. Subsequently, they would select a random sample of students from each grade level, ensuring that each stratum is proportionally represented in the overall sample.