Topic review question:
What does stratification mean in random sampling?
Stratification or stratified random sampling is a method that is used where the population of a group starts to divide into smaller groups. These sub- groups are known as strata. When you stratify a population, you begin to create different layers. This has been known to improve the representation of each group in the population. This gives the researchers to best representation from the entire sample being studied. Although stratified random sampling does differ from simple random sampling. That involves the entire population’s random selection of data. That means each type of sample is likely to occur. Stratification is not just a mathematical type of method. “It uses more logic to get the understanding of concepts and issues to result in high-quality work.” (Richmond, McCroskey, Powell, 2013)
Richmond, V. P., McCroskey, J. C., & Powell, L. (2013). Organizational communication for survival. Pearson.
I really like how you broke it down what stratification in random sampling means. It made it easy to understand. It was interesting how you also used the example of all the different layers for the stratification.
Before reading this chapter I never realized how important sampling was, especially in the field of informatics. This class has been really good in showing all the different aspects of informatics.