| Jason Brinkley |
Creating synthetic data via simulation can often be a powerful tool for a wide variety of analyses. The purpose here is to
provide a basic overview of simulating data using the SAS Data step for single and multiple variables of different types for
a variety of purposes. Focal points are in creating correlated variables and the general methodology of Monte Carlo
simulation. Examples will include power calculations, sensitivity analysis, and exploring nonstandard analyses.
The workshop is designed for the mid-level analyst who has basic knowledge of data management, visualizations and
basic statistical analyses such as correlations and t-tests. |