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  6. JMP Pro

JMP Pro

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last updated:Apr 20, 2026

SAS Institute Japan JMP Japan Division
SAS Institute Japan JMP Japan Division
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Sophisticated methods for conducting advanced analysis.

JMP Pro is software that adds advanced analytical capabilities to JMP. The statistical analysis software JMP Pro, provided by SAS, is designed for scientists and engineers and includes familiar excellent features such as visual data access, data manipulation, interactive operation methods, a wealth of analytical functions, and scalability, along with numerous advanced techniques. Furthermore, JMP Pro offers a variety of advanced tools. It includes predictive modeling with validation features using various different methods, state-of-the-art modeling techniques, model comparison and averaging, advanced multivariate analysis, reliability block diagrams, coverage arrays, mixed models, uplift models, and statistical methods utilizing advanced calculators. With JMP Pro, you can perform sophisticated and diverse analyses, helping to remove barriers that hinder statistical discoveries and uncover clues hidden in the data. This enables you to more quickly find breakthroughs in problems and anticipate and control the future.

    Production Management SystemProcess Control SystemBusiness Intelligence and Data Analysis
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JMP Pro

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Main Features of JMP Pro ■ Predictive Modeling and Cross-Validation: Effectively build and validate models ■ Model Comparison: Determine the best model for the problem at hand ■ Formula Depot and Score Code: Organize models in the formula depot and save model score codes ■ Connection to SAS: Access the SAS system and integrate data ■ Cutting-Edge Modeling: Build excellent models even with complex data ■ Reliability Block Diagram: Fix system vulnerabilities and avoid future failures ■ Simulating Repairable Systems: Simulate repair events to understand downtime, repair frequency, and costs ■ Coverage Arrays: Plan experiments to maximize defect discovery rates while minimizing costs and time ■ Mixture Models: Analyze time and space-related data when multiple subjects are measured or variable groups are correlated ■ Uplift Models: Predict customer segments likely to respond to certain actions for targeted marketing ■ Advanced Computational Techniques: Exact tests, nonparametric exact tests, bootstrap methods ■ Sharing Results: Share results through videos, 3D graphs, and interactive reports

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Applications/Examples of results

JMP Pro Applicable Fields (Example) ■ Customer Relationship Management (CRM) - Preventing service cancellations - Proposing cross-sell & upsell opportunities - Customer segmentation ■ Manufacturing - Improving manufacturing processes - Enhancing product reliability/quality ■ Pharmaceuticals - Screening lead compounds - Improving quality in pharmaceutical processes ■ Banking and Insurance - Credit risk management - Fraud prevention ■ Healthcare - Predicting treatment effects - Disease diagnosis

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Example of building a classification model for food identification using spectral data with the statistical analysis software JMP Pro.

Example of building a classification model for food identification using spectral data with the statistical analysis software JMP Pro.

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Bayesian optimization is not just about "a small number of experiments" – understanding its strengths through a comparison with experimental design methods.

Bayesian optimization is not just about "a small number of experiments" – understanding its strengths through a comparison with experimental design methods.

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Trend Score Matching Using the Statistical Analysis Software JMP Pro: A Practical Approach on the "Causal Treatment Effect" Platform

Trend Score Matching Using the Statistical Analysis Software JMP Pro: A Practical Approach on the "Causal Treatment Effect" Platform

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Verification of the effectiveness of Lasso regression using the statistical analysis software JMP Pro through simulation - For data with multicollinearity.

Verification of the effectiveness of Lasso regression using the statistical analysis software JMP Pro through simulation - For data with multicollinearity.

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Consideration of pharmacokinetic models when varying covariates: Practical example using statistical analysis software JMP.

Consideration of pharmacokinetic models when varying covariates: Practical example using statistical analysis software JMP.

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Bayesian optimization

Utilization of the experimental design features of the statistical analysis software JMP in the manufacturing industry.

  • Seminar・Event

JMP is a software that not only excels in statistical analysis and graph creation but also has robust features for experimental design. By utilizing experimental design, efficient data collection can be achieved while keeping time and costs down. In this seminar, we will focus on the features of experimental design, specifically the sample size explorer and Bayesian optimization, and present examples of their application in the manufacturing industry in a demonstration format. [Overview] First half: Utilization of t-tests in the manufacturing industry and simulation of required data numbers We will explain the overview and examples of t-tests, which are used for various purposes in the manufacturing industry, and introduce analysis examples using JMP. Additionally, we will demonstrate how to simulate the relationship between the required data numbers for t-tests and statistical power using the sample size explorer. Second half: Utilizing JMP Pro Bayesian optimization - Application to simulation experimental data The Bayesian optimization platform is originally designed for experimental data that includes measurement errors; however, there is also a significant demand to apply it to simulation experimental data that does not include errors, such as CAE. In this seminar, we will introduce approaches for utilizing Bayesian optimization with simulation experimental data.

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SAS Institute Japan JMP Japan Division

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The JMP story goes back to 1989 when John Sall decided to combine statistical analysis capabilities with graphical visualizations to animate and visualize data. For more than 35 years now, John Sall has led JMP R&D, making each version of JMP more visual, more interactive, and more practical to help users understand their data. What started as a passion project has grown by leaps and bounds. It’s now a family of statistical software products designed with scientists and engineers in mind and used worldwide in nearly every industry.

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