What is an example of stratified sampling?

A stratified sample is one that ensures that subgroups (strata) of a given population are each adequately represented within the whole sample population of a research study. For example, one might divide a sample of adults into subgroups by age, like 18–29, 30–39, 40–49, 50–59, and 60 and above.

What are the two types of stratified random sampling?

There are two types of stratified sampling – one is proportionate stratified random sampling and another is disproportionate stratified random sampling. In the proportionate random sampling, each stratum would have the same sampling fraction.

What is an example of random sampling?

An example of a simple random sample would be the names of 25 employees being chosen out of a hat from a company of 250 employees. In this case, the population is all 250 employees, and the sample is random because each employee has an equal chance of being chosen.

Where is stratified random sampling used?

Stratified random sampling is typically used by researchers when trying to evaluate data from different subgroups or strata. It allows them to quickly obtain a sample population that best represents the entire population being studied.

What is stratified random sampling pattern?

Stratified random sampling is a method of sampling that involves the division of a population into smaller subgroups known as strata. In stratified random sampling, or stratification, the strata are formed based on members’ shared attributes or characteristics, such as income or educational attainment.

Why we use stratified random sampling?

Stratified random sampling is one common method that is used by researchers because it enables them to obtain a sample population that best represents the entire population being studied, making sure that each subgroup of interest is represented. All the same, this method of research is not without its disadvantages.

What is the difference between stratified random sampling and cluster sampling?

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population.

Is stratified random sampling qualitative or quantitative?

qualitative research
Stratified random sampling is more compatible with qualitative research but it can also be used in quantitative data collection. Whether you opt for proportionate or disproportionate stratified sampling, the most important thing is creating sub-groups that are internally homogenous, and externally heterogeneous.