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.

Why is stratified sampling better than random?

Stratified sampling offers some advantages and disadvantages compared to simple random sampling. Because it uses specific characteristics, it can provide a more accurate representation of the population based on what's used to divide it into different subsets.

What is stratified sampling and when would you use it?

Stratified sampling is used to select a sample that is representative of different groups. If the groups are of different sizes, the number of items selected from each group will be proportional to the number of items in that group.