The Difference Between Stratified Random Sampling and Cluster Sampling Is

Multiple Choice

The difference between stratified random sampling and cluster sampling is that in cluster sampling:

A) a researcher must be able to secure a complete listing of the potential sampling units that make up a defined target population.
B) a large number of respondents are interviewed in a relatively short time.
C) the representativeness of a sample cannot be measured because sampling error estimates cannot be calculated.
D) the sampling units are divided into mutually exclusive and collectively exhaustive subpopulations.
E) a target population is separated into different groups.