Learn how simple random sampling works and what advantages it offers over other methods when selecting a research group from a larger population.

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.

Systematic sampling, stratified sampling, and cluster sampling are other types of sampling approaches that may be used instead of simple random sampling.

First, you must assign a unique identifier to each item. Then you can use a random number table or a computerized random number generator to select your random samples.

The following PROC SURVEYSELECT statements select a probability sample of customers from the Customers data set using simple random sampling. title1 'Customer Satisfaction Survey'; proc surveyselect ...

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, ...