A simple random sample is used to represent the entire data population. A stratified random sample divides the population into smaller groups based on shared characteristics.

Researchers generate a simple random sample by obtaining an exhaustive list of a larger population and then selecting, at random, a certain number of individuals to comprise the sample.

Researchers choose simple random sampling to make generalizations about a population. Major advantages include its simplicity and lack of bias.

When you request stratified sampling with a STRATA statement, PROC SURVEYSELECT selects samples independently within strata. The selection probability for a unit in stratum h equals nh/Nh for ...

Example 62.2: Simple Random Cluster Sampling This example illustrates the use of regression analysis in a simple random cluster sampling design. The data are from S rndal, Swenson, and Wretman (1992, ...