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Tutorials

Led by the developers of JMP, these 90-minute tutorials are a rare opportunity for you to go in-depth on specific topics with the experts themselves. You’ll learn about some of the core tenets of JMP and see the software in action. You can sign up for tutorials when you register for the conference. All sessions are €125 plus VAT.

  • Introduction to Functional Data Analysis (2019-EU-TUT-140)

    Tuesday, 12 March, 8:30 – 10:00
    Chris Gotwalt, JMP Director of Statistical Research and Development, SAS
    Ryan Parker, JMP Senior Research Statistician, SAS

    • Topic: Predictive Modeling
    • Level: 3

    JMP Pro is now able to model and visualize functional data in a new way that is direct, straightforward and leads to highly accurate models. We will introduce the Functional Data Explorer platform and go through a set of examples that illustrate two particularly useful families of problems that it facilitates solving, function response DOE analysis (FR-DOE) and functional regressor machine learning (FR-ML). FR-DOE analysis allows one to see directly how the shape of a response curve changes as a result in changes in the value of the DOE factors. FR-ML is an approach to feature extraction for sensor data from manufacturing processes that faciliates accurate early prediction of final batch yield or faulty products. Our examples will be primarily from pharmaceutical, chemical and semiconductor manufacturing, but our approach can be applied to practically any industry.

  • Advanced Data Preparation: 10 Essential Tools in JMP® to Get From “Messy” to “Analysis Ready” (2019-EU-TUT-143)

    Tuesday, 12 March, 8:30 – 10:00
    Julian Parris, JMP Learning Strategy Manager, SAS

    • Topic: Data Access and Manipulation
    • Level: 2

    Rarely, if ever, do data come to us in an “analysis ready” format. Luckily, JMP has a rich and expansive set of tools that enable you to efficiently prepare your data for analysis. In this tutorial we explore 10 of the essential tools in JMP that help us get our data from “messy” to “analysis ready,” including methods for handling table restructuring and joining, computed and derived variables, outliers and influential points, recoding of variables, missing values and more. After we explore each of the 10 essential tools in depth and discuss best practices (and even some “off-label” uses for certain tools), we’ll work through three case studies where we will apply these tools in various ways to efficiently import, recode, restructure and reorganize complex and challenging data sets. Previous experience using JMP is highly recommended, though not strictly necessary.

  • Essential Scripting for Efficiency and Reproducibility: Do Less to Do More (2019-EU-TUT-146)

    Tuesday, 12 March, 8:30 – 10:00
    Drew Foglia, JMP Life Sciences Principal Software Developer, SAS
    Evan McCorkle, JMP Software Developer, SAS

    • Topic: JSL Application Development
    • Level: 2

    From reproducing simple tasks to automating daily processes to sharing scripts with colleagues to deploying full applications across your organization, challenges exist at every level that can limit the efficiency and reliability of your JSL scripts. In this tutorial, we will travel along the arc from small scripts to large applications presenting best-practice techniques for mitigating many of the common, yet subtle, pitfalls that often hinder JSL novices and veterans alike. We will discuss strategies for combining multiple steps into a cohesive script, and conversely splitting overly large scripts into more manageable files. We will also present tips for handling errors, wrangling windows, isolating variables from unexpected changes, protecting the integrity of your scripts without compromising usefulness and more.

  • Large-Scale Process Monitoring Using JMP® (2019-EU-TUT-069)

    Tuesday, 12 March, 10:30 – 12:00
    Laura Lancaster, JMP Principal Research Statistician Developer, SAS

    • Topic: Quality and Reliability
    • Level: 2

    In this age of big data and complex manufacturing there is often an enormous amount of process data that regularly needs to be monitored and analyzed to maintain or improve quality. It can be difficult for analysts to keep up with the demands of monitoring so much data with limited time and resources. JMP has several tools to help the analyst quickly and efficiently increase the scale of their process monitoring. The Process Screening platform in JMP allows users to easily scan large numbers of processes for stability and capability and enables them to quickly focus attention on processes that need improvement. This saves time, reduces workload and improves quality. The platform initially computes a summary report based on control chart, capability and stability calculations and creates several graphs for quick visual assessment of the health of many processes. Based on these initial results, it is easy to select the processes that need attention and explore them more in depth with easy access to Control Chart Builder and the Process Capability platforms. The Response Screening platform in JMP allows users to test many process measurements for the effects of a process change with adjustments to guard against incorrect declarations of significance. The platform initially produces results and summary statistics in data tables along with several easily interpretable plots in a report to enable further exploration of significant results. This talk will use case studies to demonstrate how to use JMP to monitor and analyze many processes for fast and efficient improvement.

  • Formula Editor Deep Dive (2019-EU-TUT-123)

    Tuesday, 12 March, 10:30 – 12:00
    Mike Muhlada, JMP Senior Test Engineer, SAS
    Audrey Shull, JMP Senior Testing Manager, SAS

    • Topic: JSL Application Development
    • Level: 1

    This demo will use examples to explain Formula Editor mechanics, to investigate and fix common errors, and to solidify best practices and useful tricks for formula creation. A detailed walk-through will cover various aspects of the formula builder, including using drag and drop, keyboard shortcuts and function buttons to create formulas. As we work through the examples, we will discuss useful functions, uncover and correct common mistakes, work with subscripts and more. Best practice topics to be covered include: custom formats, using formulas for data cleanup, column transforms and using intermediate columns to build more complex formulas. Special emphasis will be placed on JMP 14 new features, including user-defined functions, result preview, live formula error/warning detection and customizable function list.

  • The Fundamentals of Modern Experimentation Using JMP® (2019-EU-TUT-147)

    Tuesday, 12 March, 10:30 – 12:00
    Bradley Jones, JMP Distinguished Research Fellow, SAS

    • Topic: Design of Experiments
    • Level: 1

    Designed experimentation is the best way to learn about industrial processes. But, in the long history of the design of experiments, most experimenters learned methods that focused on conforming the experiment to classical designs. The need to understand these constraints limited the number of effective experimenters. JMP’s approach to DOE takes the burden of understanding the constraints of textbook designs off the practitioner, instead putting the experimenter in control. See how to use the Custom Designer to design an experiment for any process. The Custom Designer creates an experiment tailor-made for your situation. Do you have constraints on the input factors? No problem. Mixture factors along with process inputs? No problem. What about a run budget that limits the number of experiments you can perform? The Custom Designer will give you a design that will allow you to learn as much as possible within your budget. A few years ago Stu Hunter said that, "[the technology behind the DOE platforms in JMP] would change the way I teach DOE”. Come see how.

  • The Most Flexible Modeling Platform That You're Not Using (2019-EU-TUT-142)

    Tuesday, 12 March, 13:00 – 14:30
    Clay Barker, JMP Principal Research Statistician Developer, SAS

    • Topic: Predictive Modeling
    • Level: 2

    Generalized Regression - it sounds scary, but it's not. This platform in JMP Pro can handle most common linear modeling exercises. Need to find the best set of predictors in a sea of possibilities (i.e., variable selection)? This platform can do that. Need to model a categorical response with more than two levels? Generalized Regression can do that. Have problems with non-normal responses like count data or yield percentage? Where other modeling methods fall down with these responses, Generalized Regression handles them with aplomb. If you're not using this platform, you're missing out. We will look at using Genreg to build models in a variety of settings: starting with an orthogonal designed experiment and moving to large observational data sets.

  • Automated Report Creation: From Data Import to Publication (2019-EU-TUT-079)

    Tuesday, 12 March, 13:00 – 14:30
    Brian Corcoran, JMP Director of Research and Development, SAS

    • Topic: Data Access and Manipulation
    • Level: 1

    JMP is a powerful analysis and visualization tool, but it is often only part of the workflow. Data can reside in a database or in an Excel file. The consumers of your report may not have JMP and may not want to know the details of producing the end result. Finally, you may need to have this task done every day, automatically. This talk looks at an end-to-end automating of report creation using JMP Query Builder, JSL, Graph Builder, and publishing to JMP Journals, interactive HTML and even JMP Public with help from the operating system task scheduling mechanism.

  • Graph Builder: From Discovery to Presentation (2019-EU-TUT-144)

    Tuesday, 12 March, 13:00 – 14:30
    Bill Worley, JMP Senior Systems Engineer, SAS

    • Topic: Data Visualization
    • Level: 1

    Graph Builder is a jack-of-all-trades when it comes to visualizing your data. It is useful throughout the analysis process, from exploring your data to understand what you've got, to discovering relationships, to crafting the perfect graph to present your results. This session will show you how to use Graph Builder effectively with an overview of the graph elements available and the options for each one. It will also show you some tricks to help you become a master graph builder.

  • Introduction to Machine Learning With JMP® Pro (2019-EU-TUT-141)

    Tuesday, 12 March, 15:00 – 16:30
    Chris Gotwalt, JMP Director of Statistical Research and Development, SAS

    • Topic: Predictive Modeling
    • Level: 3

    In this tutorial we will give a general overview of how to apply machine learning methods using the tools in JMP Pro. The essential idea is that the basic tools of machine learning actually make modeling easier than earlier approaches to modeling data. We will begin by introducing the basic concepts of how models are chosen in a machine learning framework, then show how to set that up with the Make Validation Column utility. Then we will demonstrate ADI, a new approach to missing data imputation that has been added to JMP Pro 14. After that we will illustrate the most important platforms for machine learning in JMP Pro: Neural, Partition and Generalized Regression. At the end we will use Model Comparison to make a final decision about what model to use and use the Formula Depot to create scoring code to use the model outside of JMP Pro. Throughout we will illustrate the unique interactivity in JMP and its close association between data and graphs, which makes the modeling decision process intuitive and transparent, while also also letting one "see inside the black box" of machine learning models in a way that no other product can.

  • JMP® Projects: A New Way to Organize Your Work in JMP® 14 (2019-EU-TUT-145)

    Tuesday, 12 March, 15:00 – 16:30
    Aaron Andersen, JMP Principal Software Developer, SAS
    Bernd Heinen, JMP Senior Systems Engineer, SAS

    • Topic: Data Exploration
    • Level: 1

    Many JMP users have experienced an interactive JMP session that left them with many windows and analyses reports opened all at once. While using JMP in this "floating window mode" may work for many, there are situations where having a tabbed interface is preferred. Users also may want to associate certain files with an analysis project and not have the full list afforded by the Home Window. For these reasons, we created the JMP project in JMP 14. Projects provide a single document interface to JMP, a tabbed, re-configurable work space, a place to bookmark files and a window list that lets the user easily navigate various open windows, data tables, scripts and more, as well as launch supporting files like PDFs and PPT documents. Projects can also be used to quickly open and close many files associated with one or more individual analysis activities and can be used to keep parallel projects separate where in the past you may have needed to run multiple JMP sessions. Finally, projects in JMP 14 can also give you an easy way to share and collaborate on work with their archiving functionality.

  • Getting the JMP® on Your Clinical Trial Analysis (2019-EU-TUT-091)

    Tuesday, 12 March, 15:00 – 16:30
    Kelci Miclaus, Senior Manager Advanced Analytics R&D, JMP Life Sciences, SAS
    Valérie Nedbal, JMP Senior Systems Engineer, SAS

    • Topic: JSL Application Development
    • Level: 2

    The latest JMP Clinical version 7.0 was released in fall of 2018. JMP Clinical is a vertical solution leveraging JMP capabilities and an extensive JSL infrastructure to create a customized interface for clinical trial data reviews for medical safety, early efficacy, data integrity and oncology analysis. JMP Clinical 7.0 represents significant enhancements that take advantage now more than ever of key features in JMP 14. In this presentation, we will present an overview of the new features of JMP Clinical, focusing heavily on a new comprehensive review subject filter built around virtually joined JMP tables using row state synchronization (new in JMP 14) and data filters. Our JMP Clinical reviews provide standardized, reproducible analyses and now we also introduce an infrastructure for saving further JMP customizations into our reports to allow you to tie in your own JMP analyses to our applications. We also highlight new features in JMP Graph Builder to provide highly customized visualizations for solid tumor oncology clinical trial analysis, including swimmer plots, waterfall plots and spider plots. More generally, we will discuss how this vertical solution exemplifies building robust applications via JSL and the JMP add-in architecture to enhance the use of JMP.

  • Beginner: 1
  • Intermediate: 2
  • Advanced: 3
  • Power user: 4

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