Statistics interview question: What is the difference between stratified and cluster sampling?
A couple of years ago I wrote a blog post on the four different types of probability sampling techniques and that post can be read here:- https://medium.com/@tracyrenee61/interview-question-what-are-the-four-types-of-probability-sampling-d0050ce56ea1
In this post, I am endeavouring to delve deeper into two types of sampling, being stratified and cluster sampling.
Stratified sampling
Stratified sampling is a method to divide the target population into specific groups. Members from those groups are randomly selected to be a part of a study.
The use of stratified sampling can create homogeneous groups to meet certain criteria.
If a population has natural differences, it is best to use stratified sampling techniques to divide it.
Stratified sampling is preferred when the differences in individual groups will affect the study’s outcome.
Examples of stratified sampling include:-
- A target population can be identified by age, gender, or other criteria to decide which individuals would be receptive to purchasing a new product.
- Employees can be separated into groups, such as job description of…
