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Intermediate
Monitoring, Diagnosing and Improving Large-Scale Complex Processes
July 10, 2020 | 2 p.m. ETSee how to examine the impact of factor interaction and improve processes with hundreds or thousands of highly-correlated parameters. Learn to use the JMP 15 Model Driven Multivariate Control Chart (MDMCC) platform, along with Principal Component Analysis (PCA) and Partial Least Squares (PLS), to improve processes and monitor multivariate process variation over time.
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Intermediate
Screening and Controlling Manufacturing Processes
July 17, 2020 | 2 p.m. ETUnderstand how to use JMP to evaluate the Voice of the Process (process performance) and Voice of the Customer (process adherence to customer specifications). See how to monitor and analyze large amounts of data necessary to maintain or improve quality. Learn how to import process data and along with their specification and control limits to scan processes for stability and capability so you can focus attention on processes needing improvement.
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Advanced
Using JMP® Pro to Model Functional Data
July 23, 2020| 2 p.m. ETSee how to preprocess functional data and use the results to build surrogate models; analyze the surrogate models using PCA (Principal Component Analysis); and use PCA results for subsequent modeling.
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Basic
Basics for Using Graph Builder
July 24, 2020 | 2 p.m. ETLearn how Graph Builder lets you explore data dynamically until you find the visualization that best communicates the story in your data. See how to drag and drop to different zones, change graph styles, and undo and redo with agility. A case study shows you how to play with, drill into and run graphical analyses on your data.
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Advanced
Building Predictive Models for Spectral Data
July 30, 2020 | 2 p.m. ETSee how modern techniques are used to create predictive models using fewer spectra, thereby increasing efficiency and lowering cost. Learn how to use Functional Data Explorer (FDE) and Covariate Design of Experiments (DOE) to build and analyze predictive models using one-fourth to one-third of the data that would be necessary using other model-building techniques.
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Basic
JMP® Clinical: Conducting Medical Safety Reviews of Clinical Trials
August 7, 2020 | 2 p.m. ETThis session is for JMP Clinical users interested in using interactive graphics and statistical summary reports to help evaluate safety signals and early evidence of the benefit of the tested drug in ongoing clinical trials. See examples of how to use JMP Clinical to examine adverse events, abnormal findings and drug efficacy indicators to help expedite the review, analysis and reporting of clinical trials.
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Intermediate
Using Formulas to Get the Most Value from Your Data
August 14,2020 | 2 p.m. ETSee how JMP's powerful, easy-to-use Formula Editor lets you create columns whose values are computed by a formula and then store the formula as part of column information. Learn how to build formulas that are simple assignments of numeric, character, or row state constants, or that contain complex evaluations based on conditional clauses. See how formulas that are linked to, or dependent on, values in other columns and how those values will be automatically recomputed when values change.
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Intermediate
Building and Comparing Predictive Models using JMP Pro®
August 21, 2020 | 2 p.m. ETLearn about model types and techniques; the roles of test, training and validation data; and how to compare models. See how to build, validate and compare models to predict disease risk using disease and demographic data using JMP Pro.
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Advanced
Handling Constraints When Designing Experiments
August 27, 2020 | 2 p.m. ETLearn JMP advanced Custom DOE approaches for exploring multifactor opportunity spaces. See a case study that shows how to handle linear constraints, use blocking and successfully address hard-to-change factors in your design.
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Intermediate
Extracting Practical Information from Quality-by-Design Models
August 28, 2020 | 2 p.m. ETSee how to design and execute structured experiments to efficiently design and manufacture pharmaceutical and medical devices. Learn how to address the influence of real-world variation patterns when simulating and determining settings of critical process parameters that meet the requirements for critical quality attributes.
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Advanced
Machine Learning and Biomarker Sub-Group Analysis for Precision Medicine
September 3, 2020 | 2 p.m. ETRoutinely including genomic and other biological data in clinical research, practice and care is increasingly transforming decision making processes in precision medicine and prediction health. For example, the FDA reports that pharmacogenomic biomarkers are now included in drug labeling of over 400 drugs. Learn how modern machine learning and statistical techniques can be applied for prognostic (e.g. to determine if a patient should receive treatment) and predictive (e.g. to determine patient outcome or risk to given treatment) analytic approaches to biomarker discovery for precision medicine and health. See how to use JMP Genomics machine learning and subgroup exploration capabilities to model the traditionally wide genomic data problems that contain many thousands of DNA, gene, metabolite or protein signatures.
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Basic
Essentials of Designing Experiments Using JMP
September 11, 2020 | 2 p.m. ETSee how to design a controlled set of tests to model and explore the relationship between factors and one or more responses. Learn about the basic types of experimental designs and related terminology essential to making experimental decisions. See two case studies that demonstrate how to build, model, refine and interpret results.
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Intermediate
Creating Custom Drill-Down Graphs to Enhance Interactive Reporting
September 18, 2020 | 2 p.m. ETSee how to use JMP graph hover labels to get instant details about data points without leaving the graph. Learn how to create, save and share a series of drill-down enabled customized hover labels to display graphlets and gridlets that provide immediate context while keeping you in the analysis flow.
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Advanced
Designing Experiments to Optimize Manufacturing Materials Selection
October 8, 2020 | 2 p.m. ETSee how to design experiments based on physical or chemical properties to significantly minimize the number of required experimental conditions and produce a model that can predict untested options. These efficient designs are based on QSAR (Quantitative Structure – Activity Relationship) and a 2017 JMP Discovery Summit presentation by Silvio Miccio, Procter and Gamble.
Prerequisites to get the most from Mastering JMP:
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