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  • Learn how to build custom Python data connectors and further customize JMP’s Data Connector Framework with the Python Data Connector Demo, available now in the JMP Marketplace!
  • See how to create experiments to support product design and ID useful product features. Register for June 12 webinar, 2pm US Eastern Time.

Learn JMP Events

Events designed to further your knowledge and exploration of JMP.
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  • Thank You Philippines! 2026 JMP Philippines Seminar Highlights & Materials

    A big thank you to everyone who joined our recent JMP Philippines Seminar! It was a fantastic session with strong participation and engaging discussions. One of the key highlights was the real-world case sharing by our JMP Champion, Neil Pelayo (Ms Barbie), who shared valuable practical insights and industry experiences. The session also featured a demonstration by our JMP Systems Engineer of the ...

    Southeast Asia JMP Users Group |
    Apr 6, 2026 1:45 AM
    266 views | 0 replies

  • Salt Lake City JMP Users Meetup April 15, 2026

    Join the Salt Lake City JMP Users Group for an afternoon of community impact and outdoor fun.

    We’ll kick things off with a short, hands-on service project, and then head into a beginner-friendly disc golf experience at a local park.   Give back. Get outside. Connect with your JMP community.   Date: April 15
    Time: 1:30 PM – 4:00 PM MDT
    Location: Riverbottoms Disc Golf Course, 12127 S Vahe St, Riverton...

    131 views | 0 replies

  • Reduce manufacturing-related operating costs by shortening the testing period

    For decades, testing was limited to 2% of total manufacturing costs with highly advanced automated test equipment capable of performing several different tests at the same time on multiple chips or wafers, and ultimately for different functions as part of system-level testing.

    Today, these testing percentages are on the rise again. 

    Based on run-on-error data and test time data, it is easy to obta...

    170 views | 0 replies

  • Why NXP can reduce testing costs while delivering on high quality & reliability standards: Customer Success Story

    NXP's Citizen Data Scientist Program is an initiative that delivers both statistical training and tangible results – like eliminating more than 100 tests without losing reliability coverage – to the business. In this video, Mehul Shroff, Technical Director for Intrinsic/Radiation Reliability at NXP, explains how statistical approaches in place at NXP mean cost reduction doesn't come at a cost to...

    158 views | 0 replies

  • JMP Hands-on Exercise Materials - Six Sigma project

    We’re excited to share a set of JMP hands-on exercise materials with the community! Feel free to download and explore them at your own pace. Please Download the JMP Add-ins and JMP Journal in Advance:
    To fully participate in the exercise, kindly download the following materials: 1. Capability Explorer Add-in: https://marketplace.jmp.com/appdetails/Capability+Explorer  2. Modern Six Sigma Add-in: ht...

    Southeast Asia JMP Users Group |
    Mar 24, 2026 2:22 AM
    233 views | 0 replies

  • JMP Ireland Users Group 2026 registration NOW OPEN!

    Registration is now open for the upcoming Ireland Users Group at the University of Limerick. Register now to meet experts from JMP, see presentations from external partners, and network with like minded people. There is also still time to present, so if you'd like to, let me know: christopher.sanger@jmp.com You wont want to miss this, so register here today: Ireland JMP Users Group 2026 | JMP  

    Irish JMP Users Group Discussions |
    Mar 23, 2026 6:55 AM
    156 views | 0 replies

  • On-Demand Webinar: Fab Data, Fast Insights: Analytic Workflow for Semiconductor Engineers

    In this on-demand webinar, discover how JMP helps semiconductor manufacturers and Tier 1 suppliers respond faster to excursions, uncover root causes, and drive improvements in yield and quality. Learn more about JMP’s capabilities in process monitoring, interactive data visualization, predictive modeling, and workflow automation – tools that streamline decisions and scale insights across operation...

    190 views | 0 replies

  • JSL 4.0

    Does it make sense to use the Scripters Club platform to discuss new and future enhancements to JSL? The aim would be to organize ideas, inform people about new features, and advertise future improvements.

    Game Changers: Expression Handling9Data table subscripting 13Add-In Manager2017Python and R embedded 18Migrate to new JSL code editor  Comprehensive scripting index  chatty mode() for AI debuggin...

    JMP Scripters Club Discussions |
    Mar 9, 2026 3:16 PM
    2912 views | 13 replies

  • How JSR Micro Boosted Quality & Efficiency with Advanced Analytics

    I’m sharing this success story from JSR Micro because it’s a strong example of how the right analytics strategy can create measurable impact in semiconductor manufacturing. In this case, JSR Micro streamlined its quality control and production analytics by integrating multiple data sources using solutions from JMP. Faced with disconnected production, QC, and environmental datasets, the team consol...

    211 views | 0 replies

  • 🔧 Semiconductor Toolkit JMP Extension

    Hi everyone, just sharing a useful resource for those working with wafer and die data: the Semiconductor Toolkit (STK) available on the JMP Marketplace. The toolkit offers specialized wafer visualizations, tools for working with patterned and bare wafer maps, options to annotate graphics with wafer geometry, and methods to explore die‑level defect patterns or compare wafers. It also includes seve...

    203 views | 0 replies

  • Getting Started with JMP: On Demand Course

    Click the Begin! button below to start, or click Resume to return to where you left off. You can watch the videos in order, or jump to specific topics using the navigation pane on the left. Download the Getting-Started-data.zip file linked above to follow along with the demonstrations. The Big Class.jmp data file is used in the introductory videos. In these videos you'll learn about: the four com...

    Learning Library |
    Feb 23, 2026 3:00 PM
    208484 views | 18 replies

  • Custom Design of Experiments Course

    We’re excited to bring you this free e-learning course on Custom Design of Experiments. This course focuses on the core principles of designing an experiment, enabling you to understand and apply those principles to achieve an optimal design using the Custom Design platform in JMP.   Custom design is an approach to designing experiments that produces optimal designs for the problem you’re trying t...

    Learning Library |
    Feb 23, 2026 2:57 PM
    34484 views | 11 replies

  • Six Sigma at Speed: Visual DMAIC Tools for Modern Six Sigma

    The Define and Measure phases form the foundation for setting a Specific, Measurable, Achievable, Relevant and Time-bound (SMART) Six Sigma project goal. These phases ensure the objectives are clear, feasible and aligned with broader organizational priorities. Today’s data-rich environment demands Six Sigma tools that are faster, clearer, and more interactive. In this webinar, discover how modern ...

    Modern Six Sigma Discussions |
    Feb 20, 2026 1:18 AM
    144 views | 0 replies

  • Resources Quality and Process Engineering

      From the Marketplace (JMP extensions) Modern Six Sigma : Modern Six Sigma Capability Explorer: Capability Explorer Neural Network Tunning for JMP Pro: Neural Network Tuning for JMP® Pro Resource Center: Quality and process engineering   White Papers The Use if Designed Experimentation to Improve and Accelerate the Innovation Process: DOE improves and accelerates innovation Moving from Minita...

    Modern Six Sigma Discussions |
    Feb 17, 2026 5:14 AM
    162 views | 0 replies

  • Bar Charts and Frequency Tables

    Use bar charts and frequency distributons to display the distribution of categorical variables.

    Visit Discovering JMP > Visualize Your Data, Discovering JMP > Analyze Your Data > Analyze Distributions and Essential Graphing in JMP Help to learn more.

    Learning Library |
    Feb 11, 2026 1:34 PM
    484 views | 0 replies

  • Pareto Plots and Pie Charts

    Use Pareto Plots and Pie Charts to display the distribution of categorical variables. Pareto plots sort in descending order of frequency of occurrence or by a weighted value.     Creating Pareto plot and Pie Chart using Failuressize.jmp (Help > Sample Data Folder > Quality Control)   A second direct way to see pie charts For more details on creating pie charts and Pareto plots, see Discovering JM...

    Learning Library |
    Feb 11, 2026 1:12 PM
    414 views | 0 replies

  • Dot plots

    Use dot plots to display the distribution of continuous variables and include categorical variables. Dot plots allow you to assess the shape, center, and spread of the data. Dot plots are a very useful way for comparing data between groups.     Distribution of continuous variables   Add categorial variables cto compare continuous variable between groups   Visit Essential Graphing in JMP Help to l...

    Learning Library |
    Feb 11, 2026 1:12 PM
    315 views | 0 replies

  • Analyzing a Single Variable

    This Analysis Guide provides a list of potential questions that one might consider when analyzing a single variable or column of data. There are many statistical techniques useful in addressing these questions which are listed in the second column. The JMP® platforms that provide access to those statistical techniques along with One Page Step-by-Step Guides included in this manual are highlighted ...

    Learning Library |
    Feb 11, 2026 1:11 PM
    477 views | 0 replies

  • Relationship between a Single Factor and a Response Variable

    This Analysis Guide provides a list of potential questions that one might consider when studying the relationship between a single explanatory factor and a response variable. There are many statistical techniques useful in addressing these questions which are listed in the second column. The JMP® platforms that provide access to those statistical techniques along with One Page Step-by-Step Guides ...

    Learning Library |
    Feb 11, 2026 1:09 PM
    333 views | 0 replies

  • Exploring Patterns and Features

    This Analysis Guide provides a list of potential questions that one might consider when exploring data for the purpose of finding features, patterns, and overall structure in the data without the need to model the relationship between specific explanatory factors and a specific response variable. There are many statistical techniques useful in addressing these questions which are listed in the sec...

    Learning Library |
    Feb 11, 2026 1:08 PM
    299 views | 0 replies

  • Relationship between Many Factors and a Response Variable

    This Analysis Guide provides a list of potential questions that one might consider when studying the relationship between many potential explanatory factors and a response variable. There are many statistical techniques useful in addressing these questions which are listed in the second column. The JMP® platforms that provide access to those statistical techniques along with One Page Step-by-Step ...

    Learning Library |
    Feb 11, 2026 1:08 PM
    401 views | 0 replies

  • Collecting Data

    This Analysis Guide provides a list of potential questions that one might consider when trying to determine how much data to collect. For example – in designing an experiment. There are many statistical techniques useful in addressing these questions which are listed in the second column. The JMP® platforms that provide access to those statistical techniques along with One Page Step-by-Step Guides...

    Learning Library |
    Feb 11, 2026 1:07 PM
    332 views | 0 replies

  • Fitting Distributions

    This guide provides information on fitting various continuous or discrete distributions to data.  Fitting One Continuous Distribution From an open JMP data table, select Analyze > Distribution.Select one or more continuous variables from Select Columns, click Y, Columns, then click OK.
    Here we chose the variable ‘World Gross’Select Continuous Fit from the red triangle for the variable and select a...

    Learning Library |
    Feb 11, 2026 1:06 PM
    515 views | 0 replies

  • Assessing Normality

    This guide provides some ways to assess the fit of a normal distribution to a continuous variable. See options for fitting and assessing the fit of other non-normal distributions in the Fitting Distributions guide.   From an open JMP® data table, select Analyze > Distribution.Select one or more continuous variables from Select Columns and click Y, Columns.Click OK to generate a histogram (Histogr...

    Learning Library |
    Feb 11, 2026 1:06 PM
    1025 views | 0 replies

  • Introduction to the JMP Scripting Language

    This course covers the basics of scripting with JSL and then progresses to more advanced topics, including working with data tables, using matrices to facilitate computations, scripting analyses, and capturing results to make custom reports. The course also presents suggested best practices throughout.

    Learning Library |
    Feb 11, 2026 1:05 PM
    60252 views | 0 replies

  • Finding the Area Under a Normal Curve

    This guide demonstrates how to find the area under the normal curve using formulas and the Distribution Calculator. Column Formula for Area Under a Normal Curve (One Value)
    1. Select File > New > Data Table.
    2. Add one row - select Rows > Add Rows, and type “1”. Click OK.
    3. Right-click on Column 1, and select Formula to access the Formula Editor.
    4. From the function list on the left, select Probabi...

    Learning Library |
    Feb 11, 2026 1:04 PM
    486 views | 0 replies

  • Finding Standardized Values (z-Scores)

    This guide demonstrates three methods for calculating standardized values (z-scores) for a continuous variable. Method 1 (Save Standardized) From an open JMP data table, select Analyze > Distribution.Select one or more continuous variables from Select Columns and click Y, Columns.Click OK to generate a histogram and descriptive statistics.Click on the red triangle for the variable, and select Sav...

    Learning Library |
    Feb 11, 2026 1:03 PM
    864 views | 0 replies

  • Random Sampling and Random Data

    This guide demonstrates methods for selecting a random sample and generating random data. Random Sampling From an open JMP data table, select Tables > Subset.Specify how you’d like the sample to be selected: Random – sampling rate (specify the proportion).Random – sample size (specify the desired sample size).To select a stratified sample across another variable, check Stratify and select the var...

    Learning Library |
    Feb 11, 2026 1:02 PM
    752 views | 0 replies

  • Hypothesis Tests and Confidence Intervals for Proportions

    Use to estimate via a confidence interval and perform hypothesis tests for a population proportion.  Confidence Intervals for Population Proportions From an open JMP® data table, select Analyze > Distribution.Select one or more categorical variables from Select Columns, click Y, Columns (categorical variables have red or green bars).
    Note: If you have summarized data (a column with counts), enter ...

    Learning Library |
    Feb 11, 2026 1:02 PM
    432 views | 0 replies

  • Two Proportions Test and Confidence Interval

    Use to Estimate via a confidence interval and perform a hypothesis test for the difference between two population proportions. If comparing more than two proportions, refer to the Chi Square Tests for a Two-Way Table guide.  Two Proportions Test   From an open JMP® data table, select Analyze > Fit Y by X.Choose the binary response variable for the Y, Response.Choose the 2 levels variable that def...

    Learning Library |
    Feb 11, 2026 1:01 PM
    612 views | 0 replies

  • One Sample t-Test and Confidence Interval

    Use to estimate via a confidence interval or perform a hypothesis test for a population mean. Confidence Interval for the Mean 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.  Car Physical Data.jmp (Help > Sample Data Folder)                 The Upper...

    Learning Library |
    Feb 11, 2026 1:01 PM
    655 views | 0 replies

  • Chi Square Tests for a Two-Way Table

    Use to test for independence or homogeneity of two categorical variables. If comparing only two groups with a binary outcome, refer to the Two Proportions Test and Confidence Interval guide. The Contingency Table Analysis   From an open JMP® data table, select Analyze > Fit Y by X.Click on a categorical variable from Select Columns, and click Y, Response (categorical variables have red or green b...

    Learning Library |
    Feb 11, 2026 1:00 PM
    964 views | 0 replies

  • Two Sample t-Test and Confidence Intervals

    Use to Estimate via a confidence interval and perform a hypothesis test for the difference between two population means. If more than two means (more than two levels of the categorical X variable), refer to the One-Way ANOVA guide. Comparison of Two Population Means                       From an open JMP® data table, select Analyze > Fit Y by X.Click on a continuous variable from Select Columns, ...

    Learning Library |
    Feb 11, 2026 12:59 PM
    1584 views | 0 replies

  • Paired t-Test and CI

    Use to test if the populations means of two paired (dependent or correlated) samples are statistically different. Note: The paired measurements must be stored in separate columns. Paired t-Test Using Matched Pairs From an open JMP® data table, select Analyze > Specialized Modeling > Matched Pairs.Select two continuous variables from Select Columns, click Y, Paired Responses (continuous variables ...

    Learning Library |
    Feb 11, 2026 12:58 PM
    733 views | 0 replies

  • One-Way ANOVA

     Use to test for a statistical differences in comparing three or more population means. One-Way Analysis of Variance From an open JMP® data table, select Analyze > Fit Y by X.Click on a continuous variable from Select Columns, and Click Y, Response (continuous variables have blue triangles).Click on a categorical variable and click X, Factor (categorical variables have red or green bars). Click O...

    Learning Library |
    Feb 11, 2026 12:58 PM
    1084 views | 0 replies

  • Two-Way (Factorial) ANOVA

    Use to test and estimate the effect that two categorical factors and their interaction have on the population mean.  From an open JMP® data table, select Analyze > Fit Model.Click on a continuous variable from Select Columns, and click Y, Response (continuous variables have blue triangles).Click on two categorical variables from Select Columns, and click Macros, Full Factorial (categorical variab...

    Learning Library |
    Feb 11, 2026 12:57 PM
    752 views | 0 replies

  • Nonparametric Tests

    This guide illustrates how to perform a variety of nonparametric tests. For information on nonparametric correlations and measures of association, see the page Nonparametric Correlations.  One-Sample Nonparametric Tests From an open JMP data table, select Analyze > Distribution.Select one or more continuous variables from Select Columns, click Y, Columns, and click OK. The variable ‘Horsepower’ w...

    Learning Library |
    Feb 11, 2026 12:56 PM
    596 views | 0 replies

  • Bootstrapping

    This guide provides instructions on the bootstrapping technique – a resampling method for estimating the  sampling distribution of a statistic as a means to generate a confidence interval. Bootstrapping is available from many JMP reports.   Bootstrapping in JMP Report Windows From an analysis platform report window, right-click on the report of interest and select Bootstrap. In this example we us...

    Learning Library |
    Feb 11, 2026 12:55 PM
    385 views | 0 replies

  • Prediction Interval

    Use to produce an interval estimate of a single observation, a sample of n observations, or the sample mean and standard deviation of a sample of n observations. Prediction Interval for an Individual Observation 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 cl...

    Learning Library |
    Feb 11, 2026 12:54 PM
    373 views | 0 replies

  • One Sample Equivalence Test for Mean

    Use to determine if there is statistical evidence exists to demonstrate that a population mean is within a specified range (i.e., “equivalent”) to a hypothesized value.     Equivalence Test for the Mean 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.Fr...

    Learning Library |
    Feb 11, 2026 12:53 PM
    471 views | 0 replies

  • Correlation

    This guide illustrates ways to visualize the relationship between two continuous variables and quantify the linear association via. pearson's correlation coefficient. For information on nonparametric correlations, see the Nonparametric Correlations guide. Correlation Between Two Variables From an open JMP® data table, select Analyze > Fit Y by X.Click on a continuous variable from Select Columns,...

    Learning Library |
    Feb 11, 2026 12:52 PM
    1403 views | 0 replies

  • Nonparametric Correlations

    This guide illustrates how to compute nonparametric measures of association (Spearman’s Rho, Kendall’s Tau, and Hoeffding’s D). Nonparametric Correlations                                                                  From an open JMP data table, select Analyze > Multivariate Methods > Multivariate.Select two or more continuous or discrete numeric (nominal or ordinal) from Select Columns, click...

    Learning Library |
    Feb 11, 2026 12:51 PM
    451 views | 0 replies

  • Simple Linear Regression

    Use to model the bivariate relationship between a continuous explanatory variable with a continuous outcome variable. Useful to describe the relationship between the variables and to predict an outcome for different values of the explanatory variable. Simple Linear Regression Using Fit Y by X From an open JMP® data table, select Analyze > Fit Y by X.Click on a continuous variable from Select Colu...

    Learning Library |
    Feb 11, 2026 12:51 PM
    854 views | 0 replies

  • Multiple Linear Regression

    Use to model the relationship two or more continuous or categorical explanatory explanatory variables has with a continuous outcome variable. Useful to describe the relationships between the variables and to predict an outcome for different values of the explanatory variables.   Multiple Linear Regression Using Fit Model From an open JMP® data table, select Analyze > Fit Model.Click on a continuo...

    Learning Library |
    Feb 11, 2026 12:49 PM
    855 views | 0 replies

  • Stepwise Regression

    Use to perform automated variable selection in multiple linear or logistic regression models. The method is particular useful when there is a large number of candidate explanatory variables. Stepwise Regression From an open table, select Analyze > Fit Model.Select a response variable from Select Columns and click Y.Select predictor variables and click Add.If desired, select a validation column (J...

    Learning Library |
    Feb 11, 2026 12:48 PM
    719 views | 0 replies

  • Fit Non-Linear Curve

    Use to build non-linear models describing the relationship between an explanatory variable and an outcome variable.  Fit Curve Select Analyze > Specialized Modeling > Fit Curve.Select a continuous variable from Select Columns, and add to Y, Response.Select a continuous explanatory variable for X, Regressor Add a categorical variable to Group to have a separate model fit for each value of a gr...

    Learning Library |
    Feb 11, 2026 12:47 PM
    611 views | 0 replies

  • ARIMA Modeling

    Use ARIMA (Auto Regressive Integrated Moving Average) time series models to examine autocorrelation, describe patterns (trends and seasonality), and forecast future time periods.  ARIMA Modeling From an open JMP® data table, select Analyze > Specialized Modeling > Time Series.Select a continuous variable from Select Columns, and click Y, Time Series (continuous variables have blue triangles). Sel...

    Learning Library |
    Feb 11, 2026 12:46 PM
    514 views | 0 replies

  • Time Series Smoothing Models

    Use smoothing based time series models to describe patterns and forecast future time periods.  Smoothing Models From an open JMP® data table, select Analyze > Specialized Modeling > Time Series.Select a continuous variable from Select Columns, and click Y, Time Series (continuous variables have blue triangles). Select a time and click X, Time ID (optional). Click OK.  
    - A time series graph of the...

    Learning Library |
    Feb 11, 2026 12:46 PM
    637 views | 0 replies

  • Time Series Forecasting

    The Time Series Forecast platform builds a variety of different exponential smoothing models and automatically selects the with the best forecast performance. The platform is designed to forecast multiple time series. Time Series Forecast From an open JMP® data table, select Analyze > Specialized Modeling > Time Series Forecast.

    Select a continuous variable from Select Columns, and click Y (contin...

    Learning Library |
    Feb 11, 2026 12:45 PM
    533 views | 0 replies

  • Survey Analysis (Cross Tabulation)

    Categorial platform provides myriad tools to tabulate and analyze multivariable categorical data, such as that which would come from surveys. Commonly referred to as cross-tabulation, these analysis methods can be used to compare responses across multiple factors and uncover relationships between categories.  Categorical Note: The results displayed in the analysis demonstrated will be easier to i...

    Learning Library |
    Feb 11, 2026 12:44 PM
    476 views | 0 replies

  • Factor Analysis

    Factor Analysis is an analysis technique that seeks to describe the variation in a set of observed variables in terms of a smaller number of unobserved latent variables or factors.  Factor Analysis From an open JMP® data table, select Analyze > Multivariate Methods > Factor Analysis.Select continuous variables from Select Columns, and Click Y, Columns (continuous variables have blue triangles).Cl...

    Learning Library |
    Feb 11, 2026 12:43 PM
    669 views | 0 replies

  • Principal Component Analysis

    This guide provides instructions on performing a principal component analysis (PCA). This analysis method is often used to reduce the dimensionality of a data set (i.e., fewer variables) by creating a new set of variables that are linear combinations of the original variables statistically independent of each other and that capture the most information (i.e., variation and correlation) contained i...

    Learning Library |
    Feb 11, 2026 12:42 PM
    1351 views | 0 replies

  • Clustering

    Use Hierarchical or K-Means Clustering to form clusters (groups) of observations having similar characteristics. Hierarchical Clustering From an open JMP® data table, select Analyze > Clustering > Hierarchical Cluster.Select one or more numeric variables from Select Columns and click Y, Columns. Here we used the 13 numeric variables.If available, select a Label variable.Select the desired method ...

    Learning Library |
    Feb 11, 2026 12:41 PM
    903 views | 0 replies

  • Analysis of Repeated Measures (MANOVA)

    Use MANOVA (multivariate analysis of variance) for a way to analyze repeated measures data. The term repeated measures refers to data with multiple measurements taken on the same subjects, often taken over a period of time. The MANOVA platform provides tests of between and within subject effects across the repeated measurements. This example involves 16 dogs assigned to different treatment groups...

    Learning Library |
    Feb 11, 2026 12:40 PM
    626 views | 0 replies

  • Structural Equation Modeling

     Use Structural Equation Modeling (SEM) to test causal theories and analyze relationships between observed variables and underlying latent constructs. SEM combines principles from factor analysis, which identifies factors from observed variables, and multiple regression analysis, which assesses how variables relate to each other. Structural Equation Modeling Note: SEM provides a framework to perf...

    Learning Library |
    Feb 11, 2026 12:39 PM
    539 views | 0 replies

  • Repeated Measures Analysis (Mixed Model)

    This guide provides instructions on the analysis of repeated measures data using a mixed model (random and fixed effects) with nesting. The term repeated measures refers to data with multiple measurements taken on the same subjects, often taken over a period of time.    This example involves six animal subjects randomly selected from two species. The miles traveled by each animal were measured ov...

    Learning Library |
    Feb 11, 2026 12:38 PM
    1209 views | 0 replies

  • Mixed Model Analysis

    Use a Mixed Model for an ANOVA or regression model with at least one factor specified as a random variable. JMP Pro® has a Mixed Model and a Generalized Linear Mixed Model platforms offering the more flexibility in fitting mixed models. This example uses standard JMP to fit an unbalanced design involving six people chosen at random to take measurements on three different machines.   Analysis of L...

    Learning Library |
    Feb 11, 2026 12:37 PM
    1546 views | 0 replies

  • Regression Trees (Partition)

    Use to build a partition-based model (Decision Tree) that identify the most important factors that predict a continuous outcome and use the resulting tree to make prediction for new observations.  Regression Trees From an open JMP® table, select Analyze > Predictive Modeling > Partition.Select a continuous response variable from Select Columns and click Y, Response.Select explanatory variables an...

    Learning Library |
    Feb 11, 2026 12:36 PM
    431 views | 0 replies

  • Discriminant Analysis

    Build a boundary based statistical model to predict a categorical outcome (classify) as a function of multiple continuous preditor variables. Discriminant Analysis From an open JMP® data table, select Analyze > Multivariate Methods > Discriminant.Select one or more continuous variables from Select Columns, and click Y, Covariates (continuous variables have blue triangles).Click on a categorical v...

    Learning Library |
    Feb 11, 2026 12:34 PM
    787 views | 0 replies

  • Support Vector Machines - Classification

      Build a boundary based statistical model to predict a categorical outcome (classify) as a function of multiple predictor variables. SVM is able to create much more flexible boundary shapes than the Classification Tree (Partition) and Discriminant Analysis method. Support Vector Machines From an open JMP® table, select Analyze > Predictive Modeling > Support Vector Machines.Add a nominal or ordi...

    Learning Library |
    Feb 11, 2026 12:33 PM
    526 views | 0 replies

  • Support Vector Regression

     Build a boundary based statistical model to predict a continuous outcome as a function of multiple predictor variables. SVR is able to create much more flexible boundary shapes than the Regression Tree (Partition) method. Support Vector Regression From an open JMP® table, select Analyze > Predictive Modeling > Support Vector Machines.Add a continuous variable from Select Columns to the Y, ...

    Learning Library |
    Feb 11, 2026 12:32 PM
    284 views | 0 replies

  • K Nearest Neighbors

     Use a proximity-based algorithm to predict a categorical outcome (classify) or prediction the value of a continuous outcome for new observations based upon the outcomes of similar observations (i.e., their nearest neighbors). K Nearest Neighbors From an open JMP® table, select Analyze > Predictive Modeling > K Nearest Neighbors.Select a categorical or continuous response variable from Select Col...

    Learning Library |
    Feb 11, 2026 12:31 PM
    388 views | 0 replies

  • Neural Networks

    Build a network based model to describe the impact that multiple predictor variables have on an outcome and to make predictions of a categorical outcome (classify) or a continuous outcome. Neural Networks From an open JMP® data table, select Analyze > Predictive Modeling > Neural.Select a response variable from Select Columns and click Y, Response. Here we chose ‘Price’.Select explanatory variabl...

    Learning Library |
    Feb 11, 2026 12:30 PM
    423 views | 0 replies

  • Simple Logistic Regression

    Use to model the relationship a continuous explanatory variable has with a categorical outcome variable. Useful for estimating the probability of the occurrence of an event for different values of the explanatory variable.  Logistic Regression Using Fit Y by X From an open JMP® data table, select Analyze > Fit Y by X.Click on a categorical variable from Select Columns, and click Y, Response (nomi...

    Learning Library |
    Feb 11, 2026 12:29 PM
    945 views | 0 replies

  • Multiple Logistic Regression

    Use to model the relationship two or more continuous or categorical explanatory variables has with a categorical outcome variable. Useful for estimating the probability of the occurrence of an event for different values of the explanatory variables.  Multiple Logistic Regression Using Fit Model From an open JMP® data table, select Analyze > Fit Model.Click on a categorical variable from Select Co...

    Learning Library |
    Feb 11, 2026 12:29 PM
    514 views | 0 replies

  • Naive Bayes

      Use this predictive modeling technique to predict a categorical outcome (classify) as a function of multiple predictor variables. The technique classifies observations by applying Bayes’ Theorem to conditional probabilities. Naive Bayes From an open JMP® table, select Analyze > Predictive Modeling > Naive Bayes.Select a nominal or ordinal response variable from Select Columns and click Y, Respo...

    Learning Library |
    Feb 11, 2026 12:26 PM
    440 views | 0 replies

  • Creating a Validation Column (Holdout Sample)

    Use to subset the data into a set used to build a model (training) and a set used to evaluate a model's predictive performance (validation). If multiple models are fit, the best performer on the validation data is often the one chosen. At times, a third set is used (test) to evaluate the chosen model's predictive performance on new data. This is considered to be a more accurate means to evaluate a...

    Learning Library |
    Feb 11, 2026 12:25 PM
    442 views | 0 replies

  • Model Comparison and Selection

     Use this platform to summarize and compare the performance of multiple statistical models that have been fit to data. For details on fitting different statistical models, see the appropriate guides. Model Comparison – Continuous Response Example:  We use the Body Fat.jmp data to predict Percent body fat. Formulas for several models, saved to the data table, are grouped under Prediction Formulas ...

    Learning Library |
    Feb 11, 2026 12:24 PM
    524 views | 0 replies

  • Text Mining – Describe Unstructured Text Data

    The Text Explorer platform is used to explore frequently used words and phrases in unstructured text data such as text found in product reviews, social media posts, comment fields in surveys, incident reports, etc. Results are summarzied through frequency tables and word clouds. Tools such as recoding, combining terms, creating stop words, among others are available to clean the data and help targ...

    Learning Library |
    Feb 11, 2026 12:23 PM
    368 views | 0 replies

  • Text Mining – Sentiment Analysis

       The Text Explorer platform is used to explore frequently used words and phrases in unstructured text data such as text found in product reviews, social media posts, comment fields in surveys, incident reports, etc. This guide shows how to perform a sentiment analysis – a methodology that assigns numerical scores to words and phrases with the intent of quantitatively measuring the positive and n...

    Learning Library |
    Feb 11, 2026 12:22 PM
    563 views | 0 replies

  • Text Mining – Advanced Analysis Methods

      The Text Explorer platform is used to explore frequently used words and phrases in unstructured text data such as text found in product reviews, social media posts, comment fields in surveys, incident reports, etc. Additional tools are available in JMP® Pro for further analysis. The text data must first be prepared for these analyses. See the Text Explorer – Describing Unstructured Text Data gu...

    Learning Library |
    Feb 11, 2026 12:22 PM
    509 views | 0 replies

  • Association Analysis (Market Basket Analysis)

      Analyze transactional data such as product purchases and occurrence of events to identify those that are dependent upon each other or tend to occur together. Metrics such as the likelihood of items/events occuring based on the occurrence of other items/events, among others are produced. Note that the data must be in list format, where each row identifies the customer or transaction ID (in one c...

    Learning Library |
    Feb 11, 2026 12:20 PM
    394 views | 0 replies

  • Variables Control Charts – I/MR Charts

    This guide provides instructions for creating I & MR (Individuals and Moving Range) control charts using the Control Chart Builder and the Control Chart platform. I/MR control charts are used to monitor a continuous variable where the data is sampled without subgroups. I/MR Charts – Control Chart Builder From an open JMP® data table, select Analyze > Quality and Process > Control Chart Builder.Dr...

    Learning Library |
    Feb 11, 2026 12:20 PM
    916 views | 0 replies

  • 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.D...

    Learning Library |
    Feb 11, 2026 12:19 PM
    879 views | 0 replies

  • Attribute Control Charts – P and NP Charts

    This guide provides instructions on creating P and NP attribute control charts. P charts are often used to plot the proportion of nonconforming (defective) items per subgroup, while NP charts are often used to plot the number of nonconforming items p er subgroup. P Charts From an open JMP® data table, select Analyze > Quality and Process > Control Chart > P Control ChartSelect one or more continu...

    Learning Library |
    Feb 11, 2026 12:18 PM
    538 views | 0 replies

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