Analytics Power Lunch

On-Demand Webcast

Computer-Intensive Analysis: Randomization


Are you an analytics pro? See how randomization, bootstrapping, bagging and simulation can be used in significance testing and modeling to balance risk and reduce the impact of model misspecification.


The unrelenting increase in computing power over the past decades has made computer-intensive methods for dealing with variation a practical possibility. Such methods, originated by Fisher and others, have the advantage that they require fewer assumptions and can be applied in a wider range of situations than conventional parametric approaches that rely on asymptotic theory. Ian Cox, JMP Global Solutions Manager, demonstrates techniques that help you to make more reliable statistical inferences and build more useful models in the first of two webcasts on this topic.

Main Course

In many application areas, sources and volumes of data continue to grow. But in some situations, data can be in short supply. This session will examine computer-intensive techniques that allow you to get the most from your data, small or large. In this 45-minute webcast, Cox:

  • Introduces computer-intensive methods for those who have not come across them before.
  • Shows examples of "exact" tests in JMP Pro.
  • Demonstrates how easy it is to program new tests using just a little JMP Scripting Language.
  • Shows how JMP can be a powerful environment for illustrating useful results that might be difficult or essentially impossible to prove theoretically.

Sweet Treat

Finally, you’ll learn practical strategies for using the data you have to better anticipate the future, capture opportunities and avoid risks. This webcast is part of The Analytics Power Lunch for Power Users series sponsored by the JMP division of SAS.

Register now for this free Webcast.

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