What is stratified sampling in research?

What is stratified sampling in research?

What is stratified sampling? In stratified sampling, researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment, etc). Once divided, each subgroup is randomly sampled using another probability sampling method.

How is stratified random sampling used in research?

1. Define the population.
2. Choose the relevant stratification.
3. List the population.
4. List the population according to the chosen stratification.
5. Choose your sample size.
6. Calculate a proportionate stratification.
7. Use a simple random or systematic sample to select your sample.

When should a researcher use stratified random sampling?

Uses of Stratified Random Sampling

1. Stratified random sampling is used when the researcher wants to highlight a specific subgroup within the population.
2. Researchers also employ stratified random sampling when they want to observe existing relationships between two or more subgroups.

What is stratified sampling in qualitative research?

Stratified sampling is a process that first divides the overall population into separate subgroups and then creates a sample by drawing subsamples from each of those subgroups. In qualitative research, stratified sampling is a specific strategy for implementing the broader goal of purposive sampling.

Why is stratified sampling bad?

Compared to simple random sampling, stratified sampling has two main disadvantages. It may require more administrative effort than a simple random sample. And the analysis is computationally more complex.

How do you write a good analytical paper?

How to Write an Analytical Essay in 7 Steps

1. Choose a point of view.
2. Write an introductory paragraph ending in a thesis statement.
3. Carefully organize the body of your essay.
4. Craft clear topic sentences.
5. Populate your essay with evidence.
6. Provide space for contrasting opinions.