Word: Stratified Sampling
Part of Speech: Noun
Definition: Stratified sampling is a method used in research or surveys where a larger group (population) is divided into smaller groups (subpopulations or strata) based on certain characteristics. Then, random samples are taken from each of these smaller groups. This helps ensure that each subgroup is adequately represented in the overall sample.
When you want to study a large group and need to represent different parts of that group fairly, you can use stratified sampling. This method can be particularly useful when certain characteristics (like age, gender, income level, etc.) are important for your research.
Imagine you want to understand the shopping habits of all the students in a university. Instead of just surveying 100 students randomly, you could divide the students into strata based on their year (freshman, sophomore, junior, senior). Then, you could randomly select an equal number of students from each year to get a more balanced overview of shopping habits across all years.
In more advanced research, stratified sampling can be used in various fields such as psychology, medicine, and market research. Researchers might use it to ensure that specific subgroups are not overlooked, which could lead to biased results if only random sampling were used.
In other contexts, "stratified" can refer to anything that is arranged in layers or levels. For example, geological layers of rock can be described as stratified.
While there are no direct idioms or phrasal verbs specifically related to "stratified sampling," you might encounter phrases like "divide and conquer," which suggests breaking things into smaller parts to manage them better.
Stratified sampling is a useful way to gather information from different sections of a population to ensure everyone is represented.