Make breakthrough improvements to your product and process with Stat-Ease 360. This "pro" version augments Design-Expert software with additional features for advanced users. Capitalizing on the same streamlined workflow that makes Design-Expert best-in-class for design of experiments, technical professionals who are running computer experiments or want to implement Python scripting can now take advantage of all new functionality. Space-filling designs, Gaussian process models, Python scripting, and a new logistic classification node make Stat-Ease 360 a more powerful version of Design-Expert!
Stat-Ease 360 makes it incredibly easy to apply powerful multifactor testing tools. Give it a try to see what it can do for accelerating your research and making it a huge success. Download the Stat-Ease 360 brochure.
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Create Python scripts that interact with Stat-Ease 360. Make use of the entire Python ecosystem to visualize, analyze, and make the most of your data.
Analyze deterministic responses such as those from computer experiments with Gaussian process models.
These designs have many desirable properties that make them ideal for computer experiments.
Watch the Stat-Ease 360 launch webinar: The Debut of Stat-Ease 360 presented by Martin Bezener, Stat-Ease President & CTO.
Watch Python Integration with Stat-Ease 360 presented by Hank Anderson, Vice-President of Software Development.
More on-demand videos available on the Stat-Ease YouTube Channel.
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“Our elite users provided overwhelmingly positive feedback to our unveiling of SE360 at the 2021 Stat-Ease DOE Summit. Its new features, particularly the Python tools, expand the horizon of our software tremendously. Advanced experimenters get all of the powerful and intuitive features of Design-Expert, plus a lot more.”
Expand, contract, or shift your design space to hone in on an optimal area. DX13's wizard makes this easy for both process and mixture designs. Re-use existing data (or remove some) and make the most out of your experiment!
Use Poisson regression to fit more precise models when the response is count data (discrete, non-negative), such as the number of defects per unit or the number of occurrences per time period.
Easily model any response in various ways to easily compare them. Simply press the plus (+) button on the Analysis branch and try different model reduction methods or transformations. Choose the best analysis for achieving optimization goals.