Discovery Summit

Developer 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 $100 and will take place in the SAS Executive Briefing Center.

Wrangling All Your Data With Query Builder in JMP^® 13

Date/Time: Tuesday, Sept. 20, 8:30 – 10:00 a.m.
Developer: Eric Hill, JMP Principal Systems Developer, SAS

Tutorial Description: JMP 12 saw the addition of the Query Builder, a tool designed to vastly improve the experience of retrieving data from relational databases into JMP in analysis-ready form. In JMP 13, we have gone a step further: Query Builder can now be used to manipulate your JMP data tables. So, whether your data is coming from Excel, text files, a relational database, JMP data tables, or all of the above, Query Builder can now be your one tool for managing and bringing together all of this data. This tutorial will demonstrate several scenarios to help you get started and achieve proficiency.

Fitting Definitive Screening Designs (DSDs), Taking Advantage of Their Structure

Date/Time: Tuesday, Sept. 20, 8:30 – 10:00 a.m.
Developer: Bradley Jones, JMP Principal Research Fellow, SAS

Tutorial Description:  DSDs were introduced in 2011 and quickly became popular due to their many desirable features. One such feature is that the main effects of DSDs are uncorrelated with each other and also uncorrelated to all two-factor interactions and quadratic effects. Taking advantage of this structural feature of DSDs allows for fitting them in two independent steps. This tutorial provides a “peek into the black box” of this new fitting method that is built in for JMP 13. We will provide an add-in for attendees using earlier versions of JMP.

Creating Effective Visualizations Using Graph Builder

Date/Time: Tuesday, Sept. 20, 10:30 a.m. – 12:00 p.m.
Developer: Xan Gregg, JMP Director of Research and Development, SAS

Tutorial Description: This tutorial will teach basic through advanced use of JMP Graph Builder, both from an exploration perspective and a presentation perspective. We will start with the basic components: variables, roles, elements, legends, scales, and the properties of each, as well as how these components work together. We’ll cover common visualizations (points, lines and bars) and their variations, as well as specialized visualizations including filtered views, geographic maps, heat maps, contours, overlays and small multiples. From there, we’ll cover how to create rich displays within Graph Builder by reshaping data and combining graphic elements.

Integrated Process Improvement Using the Second-Generation Quality Tools in JMP^®

Date/Time: Tuesday, Sept. 20, 10:30 a.m. – 12:00 p.m.
Developer: Laura Lancaster, JMP Principal Research Statistician Developer, SAS

Tutorial Description: The second-generation quality tools in JMP – Control Chart Builder, Process Capability, Measurement Systems Analysis and Process Screening – were designed with an integrative philosophy to make quality analysis easier and more effective. For example, the new Process Capability platform was designed to reflect the type of control chart used in the statistical process control program, and a capability report was added inside of the Control Chart Builder. Similarly, the Shift Detection Profiler in the Measurement Systems Analysis platform allows quality engineers to make informed decisions about how to design their control chart methodology, taking into account their measurement system so they are alerted to process changes as quickly as possible.  Understanding how your measurement system, statistical process control program and process capability assessments fit together is key to improving and maintaining quality. The software’s unique design philosophy makes this simple and straightforward. Additionally, the ability to quickly screen large numbers of processes for stability with the new Process Screening platform will save time, reduce workload and improve quality. This tutorial will use a case study to show how to use each of these platforms with an integrated process improvement approach.

Building Dashboards and Applications

Date/Time: Tuesday, Sept. 20, 1:00 – 2:30 p.m.
Developer: Dan Schikore, JMP Principal Software Developer, SAS

Tutorial Description: This tutorial will take you through the process of combining multiple reports using JSL or the JMP Application Builder, so that the process can be repeated on the same or different data tables. You will learn how to enhance your application using data filters and parameterization, as well as manage your end-to-end workflow with import from sources such as the SQL Query Builder and output to interactive HTML. You will also learn about the new dashboard features in JMP 13, with summary report views and drag-and-drop arrangement of live reports.

Variable Selection Made Easy Using the Generalized Regression Platform in JMP^® Pro

Date/Time: Tuesday, Sept. 20, 1:00 – 2:30 p.m.
Developer: Clay Barker, JMP Senior Research Statistician Developer, SAS

Tutorial Description: Variable selection is the process of selecting a subset of relevant variables or predictors to use in modeling the response. It is a crucial task that yields simpler models that generalize better to new data, but it does not have to be a difficult process. The Generalized Regression ("Genreg") platform in JMP Pro enables you to do variable selection quickly, easily and interactively in a variety of settings (including least squares, logistic and Poisson regression). We will review the variable selection techniques available within Genreg (forward selection, Lasso and more) and then look at how the platform makes these techniques easy to employ. Examples will range from designed experiments to predictive modeling.

The U-to-the-V: A Hitchhiker’s Guide to JMP^® 13 Text Explorer

Date/Time: Tuesday, Sept. 20, 3:00 – 4:30 p.m.
Developer: Chris Gotwalt, JMP Director of Statistical Research and Development, SAS

Tutorial Description: JMP data explorers now have a new and powerful tool for their backpack: the JMP 13 Text Explorer! It has been suggested the process of transforming text into interpretable and actionable structured data is simple to explain; just tell them “a miracle occurs.” This presentation will start with an end-to-end JMP 13 Text Explorer demonstration of actual consumer goods survey data followed by a review of the technical material, unlocking the mystery of the “miracle.” We will show the construction and applications of the sparse document term matrix (DTM). The singular value decomposition (SVD) of the DTM forms two important reduced rank matrices: the V matrix associated with words (terms) and the U matrix describing the document space. Topics and themes are found by evaluating the factor loadings of the V matrix along with cluster analysis. Because the V matrix is linked to the U matrix, documents containing specific themes are easily found by sorting the corresponding column of the U matrix. We will show how the SVD method allows the columns of the U matrix to be used as structured data, just like any other variable in predictive analytics methods. We will also demonstrate Latent Class Analysis (LCA), a clustering technique that has been customized for applications within Text Explorer that is useful for identifying groups of documents that are similar to one another.

Uncovering Fraud, Misconduct and Other Data Quality Issues in Clinical Trials Using JMP^® Clinical

Date/Time: Tuesday, Sept. 20, 3:00 – 4:30 p.m.
Developer: Richard Zink, JMP Principal Research Statistician Developer, SAS

Tutorial Description: Fraud is an important subset of topics involving data quality. Unlike other data quality findings in clinical trials that may arise due to carelessness, poor planning or mechanical failure, fraud is distinguished by the deliberate intention of the perpetrator to mislead others. Despite the availability of statistical and graphical tools to identify unusual data, fraud itself is extremely difficult to diagnose. However, whether or not data abnormalities are the result of misconduct, the early identification, resolution and documentation of any lapse in data quality is important to protect patients and the integrity of the clinical trial. This presentation will describe examples from the literature and provide numerous practical illustrations using JMP Clinical.