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Re-Thinking the Design and Analysis of Experiments? (2021-EU-30MP-776)
Level: Intermediate Phil Kay, JMP Senior Systems Engineer, SAS Peter Hersh, JMP Technical Enablement Engineer, SAS Scientists and engineers design experiments to understand their processes and systems: to find the critical factors and to optimize and control with useful models. Statistical design of experiments ensures…
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ABCs of Structural Equation Modeling (2021-EU-45MP-752)
Level: Intermediate Laura Castro-Schilo, JMP Senior Research Statistician Developer, SAS James R. Koepfler, JMP Research Statistician Tester, SAS This presentation provides a detailed introduction to Structural Equation Modeling (SEM) by covering key foundational concepts that enable analysts from all backgrounds to use…
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Milking the Data at Dairygold: From Bar Charts to Neural Networks (2021-EU-30MP-735)
Level: Intermediate Kieran O'Mahony, Data Science & Analytics Manager, Dairygold In the modern world, the use of data analytics is typically more associated with industries such as finance, health care, pharmaceuticals, medical devices, semiconductors, e-commerce and the like. Rarely are the words agriculture and analytics…
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DSD DOE Augmented with Robust Design/HACCP and Neural/Boosted Tree Optimization (2021-EU-45MP-761)
Level: Intermediate Patrick Giuliano, Lead Quality Engineer, Abbott Mason Chen, Student, Stanford University OHS Charles Chen, Principal Data Scientist/Continuous Improvement Expert, Applied Materials As consumers recede from social eating to rely on satellite delivery, optimal food preparation is increasingly vital. Using…
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SVEM: A Paradigm Shift in Design and Analysis of Experiments (2021-EU-45MP-779)
Level: Intermediate Philip Ramsey, Professor, North Haven Group and University of New Hampshire Wayne Levin, President and CEO, Predictum Trent Lemkus, Ph.D. Candidate, University of New Hampshire Christopher Gotwalt, JMP Director of Statistical R&D, SAS DOE methods have evolved over the years, as have the needs and…
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JMP® 16 Updates in Time Series Platforms (2021-EU-45MP-745)
Level: Intermediate Peng Liu, JMP Principal Research Statistician Developer, SAS Jian Cao, JMP Principal Systems Engineer, SAS This talk will provide a comprehensive review of major updates in two time series-related platforms. More specifically, the updates include a forecasting performance-based model selection method,…
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Use of Functional Data Explorer in a Mixture Design for Tribological Performance Prediction (2021-EU-30MP-739)
Level: Intermediate Victor GUILLER, R&D Engineer, FUCHS Lubrifiant FRANCE Functional data creates challenges: it generates a lot of measurements, sometimes with redundant information and/or high autocorrelation, sampling frequency may not be regular, and it can be difficult to analyze the information or pattern behind the…
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Big DOE: Sequential and Steady Wins the Race? (2021-EU-45MP-775)
Level: Intermediate David Wong-Pascua, Senior Scientist, CatSci Phil Kay, JMP Global Learning Manager, SAS Ryan Lekivetz, JMP Principal Research Statistician Developer, SAS Ben Francis, JMP Systems Engineer, SAS Imagine a DOE problem with a huge number of possible treatments: 5 categorical factors with 3, 4, 4, 8 and 12…
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Model Screening: Streamlining the Predictive Modeling Workflow (2021-EU-30MP-781)
Level: Intermediate Mia Stephens, JMP Principal Product Manager, SAS Predictive modeling is all about finding the model, or combination of models, that most accurately predicts the outcome of interest. But, not all problems (and data) are created equal. For any given scenario, there are several possible predictive models…
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Thanks for the Memory
JMP has always liked remembering things about your data, but with JMP 16, remembering the actions you take becomes very empowering, helping your scripts repeat those same actions on the next set of data automatically. With JMP 16, there are many more features you will find memorable.