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Are you an analytics pro? Tune in to this complimentary live webcast, Computer-Intensive Analysis, and 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, will demonstrate techniques that help you to make more reliable statistical inferences and build more useful models.
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. Join us for this session, which will:
- Introduce randomization and permutation tests.
- Review and demonstrate bootstrapping and bagging.
- Show how simulations can be used to explore, understand or go beyond theory.
- And much more.
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 a new series, Analytics Power Lunch for Power Users, sponsored by the JMP division of SAS.
Like our software, this event is interactive, so bring your questions for Ian Cox.