.

Moreover, how do you stratify?

The process for performing stratified sampling is as follows:

1. Step 1: Divide the population into smaller subgroups, or strata, based on the members' shared attributes and characteristics.
2. Step 2: Take a random sample from each stratum in a number that is proportional to the size of the stratum.

when should you stratify data? When to Use Stratification

1. Before collecting data.
2. When data come from several sources or conditions, such as shifts, days of the week, suppliers, or population groups.
3. When data analysis may require separating different sources or conditions.

Keeping this in view, what does it mean to stratify data?

Data stratification is the separation of data into smaller, more defined strata based on a predetermined set of criteria. A simpler way to view data stratification is to see it as a giant load of laundry that needs to be sorted.

What is an example of a stratified sample?

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.