Exact Tests Data Considerations

Data. Calculating exact results can be computationally intensive, time-consuming, and can sometimes exceed the memory limits of your machine. In general, exact tests can be performed quickly with sample sizes of less than 30.

Assumptions. The asymptotic method assumes that the dataset is reasonably large, and that tables are densely populated and well balanced. If the dataset is small, or tables are sparse or unbalanced, the assumptions necessary for the asymptotic method have not been met, and you should use either the exact or the Monte Carlo method.

Related procedures. To set the random number seed so that you can duplicate results using the Monte Carlo approximation, use Random Number Seed on the Transform menu.