Partitioning a population into hierarchical groups or levels and selecting a sample from each group is known as:
A)simple random sampling.
B)stratified sampling.
C)systematic sampling.
D)cluster sampling.

Question

Quizplus · Accepted Answer

Stratified sampling allows for proportional representation of different groups within a population, which can increase the precision of estimates and reduce sampling error. This is particularly useful when the population contains distinct subgroups that may differ in important characteristics, such as age or socioeconomic status. Simple random sampling chooses a sample without consideration for subgroups, systematic sampling selects individuals at regular intervals, and cluster sampling groups individuals together randomly without stratification.

Partitioning a Population into Hierarchical Groups or Levels and Selecting