Cary, NC October 21-24
Add-ons

This session is chock-full of tips and tricks for getting more out of JMP. If you’ve already mastered the basics of using JMP, covered in Getting Started with JMP: On Demand, we’ve got a second serving of lessons to improve your efficiency and literacy with the software. One part data manipulation, one part customization tricks, one part “How do I find that?”, this session is a smorgasbord of tips to take your use of JMP to the next level.

Topics covered include:

• Data import
• Data manipulation
• Presets and preferences
• Workflow Builder
• Shortcuts and other time-savers
• Search JMP
• More JMP tips

This session is chock-full of tips and tricks for getting more out of JMP. If you’ve already mastered the basics of using JMP, covered in Getting Started with JMP: On Demand, we’ve got a second serving of lessons to improve your efficiency and literacy with the software. One part data manipulation, one part customization tricks, one part “How do I find that?”, this session is a smorgasbord of tips to take your use of JMP to the next level.

Topics covered include:

• Data import
• Data manipulation
• Presets and preferences
• Workflow Builder
• Shortcuts and other time-savers
• Search JMP
• More JMP tips

The assumptions of the general linear model Y = XB + E are all about the random term: the residuals are assumed to have constant variance (independent of the level of the response or predictor variables), be normally distributed, and independent. To make valid conclusions from your model, including interpreting p-values and predictions, the assumptions must be confirmed. This workshop teaches you how to check those assumptions and what to do when assumptions are violated.

Assumption checking involves both graphical and numeric procedures. Residual plots are useful for examining the normality of residuals; the variance of the residuals as a function of both the predictors and predicted response; and unexpected behavior over time, predictor values, or predicted values of the response.

The linear model can be altered to account for violations of the normality and constant variance assumptions, including transformations of the predictors and responses or fitting a more generalized linear model. Time trends in the residuals can sometimes be accounted for using time series models or adding blocking variables to the model. Some predictive models or nonparametric methods avoid these assumptions and could be an alternative, but linear regression models are the focus of this workshop.

You might be aware that wiggly functions can be well-approximated by polynomial models. But sometimes polynomials are not good enough, or maybe you already know the functional form of the model you want to fit. In these cases, nonlinear least squares regression can be a good method.

Through a simple example, you learn how the Nonlinear platform finds the optimal values of the model parameters. We discuss the algorithms available and how to choose one, as well as defining the function through the model library or saving your function to your model library. Multiple examples are used to illustrate the concepts. An overview of the Fit Curve platform is also included.

Scripting is one of the most common topics in discussions in the JMP User Community and is frequently featured in Discovery presentations. Have you ever wondered how to get started with scripting in JMP but weren’t sure where to start? Do you want to be able to interpret and update scripts written by your colleagues? Do you want to write your own scripts, or modify scripts written by JMP, to automate routine tasks in JMP or create custom reports?

This workshop is intended for JMP users who want to build a foundation in the JMP scripting language (JSL). Through examples, you learn how to

• Obtain (and modify) scripts written by JMP.
• Stitch scripts together with the Glue() function/operator.
• Test scripts and use the log.
• Interpret common error messages.
• Create reports with simple custom layouts.
• Use the Scripting Index.
• Access resources for further learning!

Note: This session does not cover Workflow Builder.

Scripting is one of the most common topics in discussions in the JMP User Community and is frequently featured in Discovery presentations. Have you ever wondered how to get started with scripting in JMP but weren’t sure where to start? Do you want to be able to interpret and update scripts written by your colleagues? Do you want to write your own scripts, or modify scripts written by JMP, to automate routine tasks in JMP or create custom reports?

This workshop is intended for JMP users who want to build a foundation in the JMP scripting language (JSL). Through examples, you learn how to

• Obtain (and modify) scripts written by JMP.
• Stitch scripts together with the Glue() function/operator.
• Test scripts and use the log.
• Interpret common error messages.
• Create reports with simple custom layouts.
• Use the Scripting Index.
• Access resources for further learning!

Note: This session does not cover Workflow Builder.

The Functional Data Explorer (FDE) in JMP Pro is a powerful tool for analyzing data that are curves or functions. New in JMP Pro 18, FDE adds the ability to do automatic peak detection, penalized SVD, and multivariate curve resolution. These new capabilities make FDE even more powerful for analyzing curves, particularly for spectral data. In this workshop, we briefly introduce the Functional Data Explorer platform before taking a closer look at the newest features.

Many JMP users create applications that are intended for a production environment. Production applications are not “one-offs,” rather they are applications that are among the tools that users rely on to do their jobs. Such applications need to be validated before deployment and will need maintenance, and consequently, additional validation, as different versions of JMP are installed or as the requirements for the application evolve. 

In this tutorial, we go over several aspects of software (and application) validation. We begin by discussing basic concepts before taking a deep dive into a few select topics. In the process, we discuss and demonstrate tools that are available to JMP users (i.e., platforms and add-ins) that can facilitate the validation of JMP applications. We end the tutorial with a Q&A for attendees to ask their specific questions to a panel of software validation experts and programming experts.

Note: Attendees should bring their real-world problems to ask of the panel of experts during the Q&A.