Learn JMP Events

Variables Control Charts – XBar & R/S Charts

This guide provides instructions for creating XBar & R or XBar & S control charts using the Control Chart Builder and the Control Chart platform. XBar & R or XBar & S control charts are used to monitor a continuous variable where the data is sampled with subgroups.    XBar & R Charts – Control Chart Builder From an open JMP^® data table, select Analyze > Quality and Process > Control Chart Builder....

Attribute Control Charts – C and U Charts

This guide provides instructions on creating C and U attribute control charts. C charts are often used to plot the number of nonconformities (or defects) in a subgroup that usually, but not necessarily, consists of one inspection unit, while U charts are often used to plot the number of nonconformities per unit, where the number of units per subgroup can vary.     C Charts From an open JMP^® data ...

Tolerance Interval

Use to produce an interval estimated to contain a specified proportion of a population. Tolerance Interval for Proportion (Normal Distribution) From an open JMP data table, select Analyze > Distribution.Select one or more continuous variables from Select Columns, click Y, Columns (continuous variables have blue triangles), and click OK.From the Distributions report window, select Tolerance Interv...

Process Capability Analysis

This guide provides instructions on performing a capability analysis using the Distribution and Control Chart platforms. A process capability analysis is used to evaluate the performance of a process for a continuous variable to specifications (Lower and/or upper specification limit, and/or target). See Capability Analysis for Multiple Responses guide for performing process capability analyses on ...

Capability Analysis for Multiple Responses

This guide provides instructions on performing a process capability analysis for multiple continuous process variables simultaneously. This platform produces a set of reports and graphs that are designed to compare the performance of the different process variables to each other.    The Capability Analysis Dialog                                                                               From a...

MSA Continuous Data – Gauge R&R

This guide provides instructions on creating a variability chart and performing a gauge R&R (Repeatability and Reproducibility) measurement system analysis (MSA). This analysis is designed to evaluate and certify the performance of a measurement system that produces continuous data. For information on using the EMP (Evaluating the Measurement Process) method, see the MSA Continuous Data – EMP Meth...

MSA Continuous Data – EMP Method

This guide provides instructions on performing a measurement system analysis (MSA) using the EMP (Evaluating the Measurement Process) method. This analysis is designed to evaluate and certify the performance of a measurement system that produces continuous data. Measurement Systems Analysis: EMP Method Select Analyze > Quality and Process > Measurement System Analysis.Click on a continuous variab...

MSA Attribute Data

Use to evaluate the performance of a categorical based measurement system (e.g.,  pass or fail, classification of parts into multiple categories, ordinal ratings). This analysis is often used to assess the ability of observers (appraisers) to correctly and consistently classify inspected items. Attribute Measurement Systems Analysis Select Analyze > Quality and Process > Variability / Attribute G...

Distribution Fitting (Life Distribution)

Use to model a single continuous variable with a probability distribution and estimate a variety of parameters (e.g., mean, percentiles, probabilities). This platform is designed to fit and compare many different distributions and can analyze data that is censored (incomplete). Note: Though frequently used to analyze time-to-event data, the analysis methods can be used to model any continous varia...

Survival Analysis (Kaplan-Meier Estimation)

Use to estimate survival (or failure) rates. Kaplan-Meier estimation methods (also known as  product limit estimation) is a non-parametric method and thus does not require many assumptions typically required in parametric methods (e.g., not needing to assume a specific probabiliy distribution to model the data). The method can be used with censored (incomplete) data. Note: Though frequently used ...

Accelerated Life Testing (Fit Life by X)

Use to model the relationship a factor has on the time-to-event. It is often used to model a factor that accelerates the event as a means to predict the time-to-event for normal operating conditions where failures do not frequently occur. This platform is able to analyze data that is censored (incomplete).  Accelerated Testing (Fit Life by X) From an open JMP^® data table, select Analyze > Reliabi...

DOE Full Factorial Design

This guide provides instructions on designing a full factorial experiment. A full factorial experiment in where every possible treatment combination will be studied. For analysis of full factorial experiments, see the DOE Full Factorial Analysis guide. Create the Design (Full Factorial Design) Open the platform under DOE > Classical > Full Factorial Design.Specify the Response(s): Double-click on...

DOE Full Factorial Analysis

This guide provides information on analyzing a full factorial experiment (experiments where every possible treatment combination is run). For instructions on designing of full factorial experiments, see the DOE Full Factorial Design guide. Specify the Model and Analyze From an open JMP^® table (for a completed full factorial experiment) select Analyze > Fit Model.
Note: The Fit Model platform can a...

DOE Fractional Factorial Design

This guide provides instructions on designing a fractional factorial experiment using the Screening Design platform. Fractional factorial experiments are used when it's more efficient to not perform an experimental run for every possible treatment combination as is done in a full factorial design.   Create the Design (Screening Design) Open the platform under DOE > Classical > Two Level Screening...

DOE Fractional Factorial Analysis

This guide provides instructions on analyzing fractional factorial experiments (experiments where not every possible treatment combination in a full factorial design is run) using the Fit Model platform.
Specify the Model and Analyze Experiments designed in JMP^® will have a Model script saved to the data table. The model specification window will be populated with this model. To generate the model...

DOE Screening Experiment Analysis

This guide provides instructions on analyzing screening experiments (e.g., fractional factorial) using the Fit Two Level Screening platform. Though the Fit Model platform can also be used, the Fit Two Level Screening platform produces graphs and analysis results designed for identifying the important effects in a fully saturated experiment. This example is a 20 run 2^5 screening experiment generat...

DOE - Custom Designs

This guide provides instructions on designing optimal experiments using the flexible Custom Design platform. The Custom Designer can be used for almost any experimental situation, including factor screening, optimization, and mixture problems, and can accommodate designs with hard-to-change factors and other constraints. DOE: Generating A Custom Design Select DOE > Custom Design.Under Responses, ...

Navigating the JMP interface in Microsoft Windows

This guide provides information on the Windows JMP interface. For information on creating a new data table, opening data tables, and finding help within JMP see  Opening JMP and Getting Started.   The Home Window When you first open JMP, you’ll see the Tip of the Day window.You’ll also see the JMP Home Window, which includes: Menus and toolbars (top).Recently used files (on the left).All open dat...

Evaluate and Compare Designs

Use the Evaluate Design platform to assess the properties of an experimental design. To compare alternative designs, use the platform Compare Designs. Evaluate Design Most DOE platforms in JMP provide an Evaluate Design outline to assess a design before making the design table to run the experiment. The platform Evaluate Design shows the same diagnostics for any existing design, and can also be u...

Monte Carlo Simulation

The JMP Profiler, with the Monte Carlo Simulator, can be used to optimize process performance in the presence of random variation. This enables you to estimate response distributions as a function of real-world random variation. Monte Carlo simulation is available from JMP Prediction Profilers using the Simulate red triangle option. Example Setup                                                   ...

Bubble Plot

Use a Bubble Plot to explore the relationship between two continuous variables and how the values change over time. Bubble color and size can be used to incorporate additional variables.  Bubble Plot From an open JMP® data table select Graph > Bubble Plot.Drag a continuous variable into the Y and X roles.Place one or more variables into the ID role so that labels can be added to the bubbles (opti...

Summarizing Data Using Tabulate

The Tabulate platform provides a tool to interactively construct tables of descriptive statistics.    Drag and Drop to Summarize Data From an open JMP^® data table select Analyze > Tabulate.Drag and drop variables from the column list to the drop zone for rows and columns.  Country (below, left) is in the rows drop zone – the number of observations per country is displayed.Horsepower (middle) is i...

Classification Trees (Partition)

Use to build a partition-based model (Decision Tree) that identifies the most important factors that predict a categorical outcome (classify) and use the resulting tree to make predictions for new observations.
Classification Trees From an open JMP^® table, select Analyze > Predictive Modeling > Partition.Select a nominal or ordinal response variable from Select Columns and click Y, Response.Selec...

Sample Size and Power for Two Sample Means

Use to interactively explore the relationships between Power, Sample Sizes, and Differences to Detect for testing a hypothesis comparing two population means. See the Two Sample t-test and Confidence Interval guide to learn how to perform a statistical test comparing two sample means. Sample Size and Power - Two Sample Means Select DOE > Sample Size Explorers and choose Power > Power for Two Inde...

Sample Size and Power for One Sample Mean

Use to interactively explore the relationships between Power, Sample Size, and Difference to Detect in testing a hypothesis for a single population mean. See the One Sample t-test and Confidence Interval guide to learn how to perform a statistical test for a population mean. Sample Size and Power - One Sample Mean Select DOE > Sample Size Explorers and choose Power > Power for One Sample Mean. Ch...

Box Plots

Use to display the distribution of continuous variables. Boxplots are based upon a set of summary statistics that describe the center and spread of data. Boxplots are a very useful way for comparing data bewteen groups. Box Plots – One Variable From an open JMP^® data table, select Analyze > Distribution.Click on one or more continuous variables from Select Columns, and Click Y, Columns (continuou...

Scatterplots

Use to display the relationship between two continuous variables. Multiple scatterplots can be displayed together in a matrix plot. Scatterplots – Two Variables From an open JMP^® data table, select Analyze > Fit Y by X.Click on a continuous response (or dependent) variable in Select Columns, and Click Y, Columns.Click on a continuous predictor (or independent) variable, and click X, Factor. Click...

Mapping in Graph Builder

Use the Graph Builder to create interactive maps of U.S. states, U.S. counties, and worldwide countries and provinces. JMP® ships with these shape files. Other shape files (e.g., ESRI) can be used or you create your own custom maps. Basic Mapping From an open JMP data table, select Graph > Graph Builder.Drag a shape variable from the Variables list (for example, State) to main drop zone.Drag vari...

Histograms, Descriptive Statistics, and Stem and Leaf

Use histograms, descrpitive statistics, and stem and leaf plots to summarize and display the distribution of continuous variables. Histograms and stem and leaf plots allow you to assess the shape, centering and spread of the data. Distributions from Car Physical Data.jmp (Help > Sample Data Folder)   Histogram Tips: • To change the display from vertical to horizontal (as shown), click on the red ...

Mosaic Plot and Contingency Table (Cross-tabs)

Use to examine the relationship between two categorical variables. A contingency table displays the frequency and percentages of the distribution of the data in a matrix format, while a mosaic plot graphically displays the information.  The mosaic plot is a side-by-side divided bar chart that allows you to visually compare proportions of levels of one variable across the levels of a second variabl...

Randomization Testing

This guide provides instructions on performing a randomization test (also known as a permutation test) – a resampling method for estimating the sampling distribution of a statistic to generate a confidence interval and a p-value for a hypothesis test. Randomization Testing is available from many JMP reports.   Randomization Testing Here, we describe how to conduct a randomization test for two mea...

Sample Size and Power for One Sample Proportion

Use to interactively explore the relationships between Power, Sample Size, and Alternative Proportions in testing a hypothesis for a single population proportion. See the Hypothesis Tests and Confidence Intervals for Proportions guide to learn how to test a hypothesis for a population proportion. Sample Size and Power - One Sample Proportion Select DOE > Sample Size Explorers and choose Power > P...

Sample Size and Power for Two Sample Proportions

Use to interactively explore the relationships between Power, Sample Sizes, and Alternative Proportions in testing a hypothesis comparing two independent population proportions. See the Two Proportions Test and Confidence Interval guide to learn how to perform a statistical test comparing two population proportions. Sample Size and Power - Two Sample Proportion Select DOE > Sample Size Explorers ...

JMP Data Tables

This page gives information on the structure, components and information contained in JMP data tables.   Click on File > Open to open a JMP data table. To open a file from the JMP Sample Data directory, go to Help > Sample Data Folder. A portion of the Sample Data file Companies.jmp is shown.    Portion of Companies.jmp Tables Panels The data table nameA list of table properties, table variables,...

Importing Data from Excel

This guide provides instructions on how to import data into JMP® from Excel. Opening Excel Files Directly in JMP Select File > Open.Navigate to the directory where your files are stored.     JMP will display all files that JMP can import – unrecognized files
will be grayed out. In Windows, to see a complete list of file types
JMP can read, click on the arrow next to All JMP Files.Select the Excel f...

JMP Tools

The Tools menu provides tools to help you interact with JMP output and data. Note: In Mac, tool bar appears at the top of all reports by deafult. In Windows, the menus and the toolbar are hidden by default. Click the Alt key to view. The tools can also be accessed from the Tools menu.   Windows tools     Mac tools   Using the Tools The default tool is the Arrow, or Cursor. To change tools, click ...

JMP Tables Menu

This guide provides information on the structure, components and information contained in JMP data tables along with some tools useful for cleaning and preparing data for analysis. The Tables Menu Functions Summary – Calculates summary statistics for columns in the active data table.Subset – Creates a new table that is a subset of the active table.Sort – Sorts a table by one or more columns.Stack...

Saving JMP Results

This guide provides instructions on copying JMP output to place in other applications and for saving JMP scripts to the data table. For information on creating publication-quality graphics, see the Publication-Quality Graphics – Windows or Publication-Quality Graphics – Mac guides. The Selection Tool – Copy and Paste to Another Program From any JMP output window, click the selection tool () in th...

Publication-Quality Graphics - Windows

This guide provides instructions on saving publication-quality graphics on the Windows version of JMP. For information on creating publication-quality graphics on the Mac version of JMP, see the Publication-Quality Graphics – Mac guide. For a basic approach on saving output, see the page Saving JMP Results. Saving Graphic Images From any JMP output window, click the selection tool () in the toolb...

Publication-Quality Graphics – Mac

This guide provides instructions on saving publication-quality graphics on the Mac version of JMP. For information on creating publication-quality graphics on the Windows version of JMP, see the Publication Quality Graphics – Windows guide. For a basic approach on saving output, see the Saving JMP Results guide. Saving Images From any JMP output window, click the selection tool () in the toolbar ...

Sharing Results on JMP Public

This guide provides instructions on publishing reports to JMP Public – a public website https://public.jmp.com where users can share graphs and reports that others can view and interact with outside of JMP. A SAS profile is required. Publish Reports to JMP Public From within a JMP file, open the graphs or output you wish to publish. The graph “Bubble Plot by Region” from the file: SATbyYear.jmp u...

Creating Formulas in JMP

This guide describes how to use formulas to create new variables (e.g, transformations, functions of existing
variables, perform logic operations, create patterned and random data, among others).
Method 1 (Create Formula With Formula Editor) From an open JMP data table, select Cols > New Column.Under Column Name, assign a name for the column. In this example, we name the column %profit/sales. Click...

Excel Add-In 1 (Passing Data to JMP)

Use the Excel JMP add-in to transfer data from an Excel worksheet into a JMP data table or to launch basic JMP analysis platforms from within Excel. Note: Add-in is only available for Windows Operating System. A locally installed version of Microsoft Excel must be on the computer at the time of installing JMP for the Excel Add-in to be added. The add-in will not be installed if Excel is only run ...

Excel Add-In II (Profiling Excel Models in JMP)

Use the Excel JMP add-in to visualize and explore Excel models in JMP using the Prediction Profiler. Note: Add-in is only available for Windows Operating System. A locally installed version of Microsoft Excel must be on the computer at the time of installing JMP for the Excel Add-in to be added. The add-in will not be installed if Excel is only run from a virtual environment. See Microsoft Help t...

Customizing JMP (Platform Presets)

This guide provides instructions on how to save all the customizations made to reports and graphs within a platform (as a template) so that those settings can be easily replicated in future analyses. This includes the various analyses run and red triangle options within a platform; components added to a graph, metrics displayed, modifying the style and format of graphical elements, text, among oth...

Customizing JMP (Preferences)

This guide provides information on customizing JMP. Options include general functionality, choosing specific styles (font, colors, graphical elements) to be used in graphs and reports, and specify which red triangle options are enabled/disabled as the default each time an analysis platform is run, among others.   See the Presets Guide to learn about more tools to customize JMP. Access via File > ...

Filtering Data for Analysis

Integrating JMP and Python

JMP can integrate with Python, combining JMP’s capabilities and interactive interface with Python’s additional tools. Use cases include: running a Python script directly on a JMP data table; using Python to import unsupported file types into JMP; blending Python and JMP Scripting Language (JSL) code together to combine their capabilities; creating a JMP add-in that leverages Python; using Python a...

Importing Text Files

This guide provides instructions on how to import text files (.txt, .csv, .dat, or .tsv) into JMP. Windows and Mac differences are noted.    Importing Data from Text Files Select File > Open. Navigate to the directory where your files are stored.   JMP will display all files recognized for the selected file type.
Here we would select “Text Files (*.txt; …)”.Select the text file you’d like to impor...

Statistical Process Control Course

We’re excited to bring you this free e-learning course on Statistical Process Control. The course includes many topics, some for beginners new to SPC, and some for more advanced SPC practitioners. You can choose your skill level and take the parts of the course that are most interesting to you. Lesson 1 is an introduction to SPC and quality methods.Lessons 2 and 3 contain the basics of Shewhart ch...

Statistical Decisions Using ANOVA and Regression Course

We’re excited to bring you this free e-learning course on Statistical Decisions Using ANOVA and Regression. The course includes many topics in the fundamentals of statistics, and most lessons build on the lessons before.   This is a course you should probably take in order. Lesson 1 is an introduction to Statistical Concepts, Descriptive Statistics, Inferential Statistics, Hypothesis Tests, and ...

Stability Analysis Course

This free recorded course covers stability analysis across product phases. The demonstrations were recorded in an older version of JMP, but the concepts and principles for assessing product stability remain the same. The methods shown in this course can be used in your current version of JMP, although in some cases the menu steps might have changed.   Lesson 1 defines product stability, explains t...

Classic Design of Experiments Course

We strongly recommend the course Custom Design of Experiments for the vast majority of design practitioners, which teaches a comprehensive, modern approach to design of experiments within a framework of fundamental principles of design (https://community.jmp.com/t5/Custom-Design-of-Experiments/Custom-Design-of-Experiments-Course/ta-p/654255).   This course is for anyone interested in a review of c...

Getting Started with JMP Live

Winter 2026 book club - Europe!

The European book club will be reading A Lab of One's Own: One Woman's Personal Journey through Sexism in Science by Rita Colwell and Sharon Bertsch McGrayne. Sessions will be led by Nina Chan on Fridays at 1 pm CET starting February 13. Please let Nina know by emailing nina.chan@jmp.com if you would like to join!

Recording Experimenters' Club Q1 2026

Video 1: JMP's DOE platform: A new addition to the artist's toolkit (view in My Videos) Read the blog from @BillFish828 here: https://community.jmp.com/t5/JMP-Blog/JMP-s-DOE-platform-A-new-addition-to-the-artist-s-toolkit/ba-p/919860 Question: What is the difference between Taguchi design and Orthogonal array. MOLS is a balanced fractional factorial design matrix that ensures independence between ...

Interactive Tools for Teaching and Learning

A variety of interactive tools for teaching and learning statistical concepts are available within JMP. These tools allow you to explore fundamental concepts covered in introductory statistics courses, including sampling distributions, confidence intervals, hypothesis testing, ANOVA, regression, and more. Other teaching and learning tools are available such as Quick Guides, How-To Videos, Case St...

Opening JMP and Getting Started

This guide provides instructions on creating a new data table, opening data tables, and finding help within JMP. Opening JMP 1. When you first open JMP, you’ll see the Tip of the Day and the JMP Home windows. On Mac you’ll also see the JMP Starter window. Tip of the Day gives helpful hints on using JMP.The JMP Home Window displays recently used files and open data tables and windows. See the page...

Winter 2026 book club

Here is a nice present for you: the books for the Winter 2026 edition of the JMP book club have been chosen! Anne Milley (anne.milley@jmp.com) will lead on Eve on Tuesdays at 4 pm US Eastern time, starting on January 20. Trish Roth (patricia.roth@abbott.com) and Diana Ballard will lead on The Art of Uncertainty on Fridays at 1 pm US Eastern time, starting on January 30. Please email Anne or Trish ...

Happy Holidays from JMP!

Wishing all our members a joyful holiday season and a fantastic start to 2026! We look forward to connecting with you through more meetings and learning opportunities in the coming year. As always, you’ll find information about new events in the JMP Newswire.  Thank you for being part of our community—here’s to learning, sharing, and growing together in 2026!

Frohe Feiertage von JMP!

Wir wünschen allen Mitgliedern eine fröhliche Weihnachtszeit und einen fantastischen Start ins Jahr 2026! :party_popper: Wir freuen uns darauf, im kommenden Jahr bei weiteren Treffen und Lernmöglichkeiten mit Ihnen in Kontakt zu treten. Wie immer finden Sie Informationen zu neuen Veranstaltungen im JMP Newswire. Vielen Dank, dass Sie Teil unserer Community sind – auf ein gemeinsames Lernen, Teile...

Joyeuses fêtes de la part de JMP !

Nous souhaitons à tous nos membres de joyeuses fêtes et un excellent début d’année 2026 ! :party_popper: Nous avons hâte de vous retrouver lors de nouvelles rencontres et opportunités d’apprentissage au cours de l’année à venir. Comme toujours, vous trouverez les informations sur les nouveaux événements dans le JMP Newswire. Merci de faire partie de notre communauté — ensemble, continuons à appre...

Happy Holidays from JMP!

Wishing all our members a joyful holiday season and a fantastic start to 2026! :party_popper: We look forward to connecting with you through more meetings and learning opportunities in the coming year: 27 Jan. - Q1 Experimenters' Club28 Apr. - Q2 Experimenters' Club Thank you for being part of our community—here’s to learning, sharing, and growing together in 2026!

Happy Holidays from JMP!

Wishing all our members a joyful holiday season and a fantastic start to 2026! :party_popper: We look forward to connecting with you through more meetings and learning opportunities in the coming year. As always, you’ll find information about new events in the JMP Newswire.  Thank you for being part of our community—here’s to learning, sharing, and growing together in 2026!  

New in JMP 19 Journal from December User Group Meeting

Hi all,  Thanks for attending last week. Here's the journal I used. Please reach out with any questions you have. Jed

Design of Experiments Introduction Kit

Resources for Learning JSL

There are plenty of ways to learn scripting in JMP, however most of you probably will start on a self-study path. To support you we want to provide here a collection of useful resources but also to some of our official trainings relevant to this topic. In addition you'll find at some customer presentations about how JSL changed the way they work (might worth for some arguments to convince your man...

Scripters Club Recordings: Managing Your JMP Add-Ins

In this Scripters Club session, Justin Chilton, the developer behind the popular Add-In Manager on the JMP Marketplace, will showcase how to better organize, update, and deploy your JMP add-ins. Learn how this tool can simplify your scripting workflow and improve how you manage and share your custom solutions. Video 1: Managing Your Add-Ins (view in My Videos) Video 2: Updates on add-in builder, v...

Model Validation Presentation - 12-3-2025

In JMP Pro, there are several types of model validation methods available that help ensure models are robust and predictions are stable. In this presentation, Senior JMP Systems Engineer Scott Allen walks through the different model validation options (validation subsets, cross validation, nested cross validation) and how different JMP platforms use the different methods. (view in My Videos) To di...

Association Analysis (Market Basket Analysis) Presentation - 11-5-2025

Presentation from JMP Systems Engineer Yasmine Hajar on Association Analysis, also commonly referred to as Market Basket Analysis. This tool helps uncover hidden patterns and relationships among categorical variables — something that is often overlooked when screening for key process parameters. (view in My Videos) To learn more about Association Analysis, view the documentation in the JMP Help Gu...

Files from COJUG meeting on 03 Dec 2025 in Columbus

Speakers from today's meeting should post their slides or journals as responses to this topic.

Need Guidance on Analyzing a DSD and Transitioning to an RSM Model

Hello everyone, I hope you’re doing well. I posted a question regarding DSD on JMP User community, but it was reported as spam for some reason? I will repost it here in hopes that someone might help. I’m a master’s student working on a research project that uses a Definitive Screening Design (DSD) in JMP to optimize a Vertical Axis Wind Turbine (VAWT). I have completed all 22 runs for my 8-factor ...

Recordings and discussion DOE Club Q4 2025

Introduction to JMP 19 new features with focus on Bayesian Optimization (view in My Videos) Further information: https://www.jmp.com/en/software/new-release/new-in-jmp Question 1: If we don't have historical data set, can we start a Bayesian Optimization? (view in My Videos) Victor: Yes, you can start with Space-Filling runs to cover your experimental space  Jonas : It needs at least one row in a ...

Winter 2026 JMP book club - pick a book!

We are happy to announce that JMP Women in STEM will be hosting a book club again! Between now and Dec. 19, help us choose which book(s) you would like to read and discuss. This survey will be open through December 19. After that, we will analyze the results and select book(s) to discuss. I'll post here again by December 24. You'll then be able to sign up for the book discussions, which will start...

Scripters Club Recording: R is Back Again in JMP 19 - Exploring R and Python Integration

R is making a powerful return in JMP 19, and it’s bringing Python along for the ride! Join Paul Nelson and Evan Carr from JMP Software Development team as they walk us through the new capabilities for R and Python integration in the latest release. This session will focus on how these languages now work more seamlessly with JSL, enabling more flexible and powerful scripting workflows. (view in My ...