In this lesson, we'll investigate ways to use some of the random number generators available in SAS:

• to select a random sample of observations from a larger data set
• to generate a scheme for assigning treatments to subjects in a randomized, controlled experiment
• to generate (i.e., "simulate") numbers that follow some underlying probability distribution

The random generator functions used in the lesson include:

• ranuni, which generates a number from a uniform (0, 1) distribution
• rannor, which generates a number from a standard normal distribution
• ranbin, which generates a number from a binomial (n, p) distribution
• ranpoi, which generates a number from a Poisson distribution with mean m.

Other random functions available in SAS, but not illustrated in this lesson include rancau (a Cauchy distribution), rangam (a Gamma distribution), rantri (a triangular distribution), ranexp (an exponential distribution), and rantbl (a discrete distribution with user-specified probabilities).

In accomplishing the goals of the lesson, we'll primarily take advantage of the tools that are available to us in a SAS data step, such as do loops, if-then-else statements, retain, and output statements. By taking such an approach, we have not only the opportunity to review and put into practice these useful data step techniques but also the opportunity to better understand the processes of random sampling, random assignment, and simulation. In the case of random sampling, however, in addition to using the data step, we will also use the SURVEYSELECT procedure just so that you are aware of its basic functionality for your future use. Due to the time constraints of the course and the complexity of the PLAN procedure, we will not use it to accomplish any of our random assignments. You should be aware, however, of its existence should you want to explore it on your own in the future.