JMPer Cable Current Issue (Summer 2015)

JMPer Cable is a technical publication for users of JMP software.

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Cover Story: Wide Data Discriminant Analysis

John Sall, Co-Founder and Executive Vice President, SAS

With multivariate methods, you have to do things differently when you have wide (many thousands of columns) data. So far, we have implemented SVD-based highly multivariate options in Discriminant, Principal Components, Hierarchical Cluster, and a form of missing value imputation. We are experimenting with using it further and also in exploring other similar methods useful in highly-multivariate analyses. Much of the hype around “Big Data” is about large numbers of rows, but large numbers of columns are also increasingly important.

Expression Columns in Data Tables

Craige Hales, Principal Systems Developer, SAS

JMP developers were listening when users asked to be able to add pictures in data tables to make the data more informative. JMP 12 gives you pictures and more: objects such as matrices and lists, JSL (JMP Scripting Language) code, and JSL expressions for pictures can all be kept in an expression column. Expression columns provide information for display and analysis as well as organize data and speed up scripts.

Process Capability in JMP^® 12

Laura Lancaster, Principal Research Statistician Developer, SAS

Process capability analysis is an essential part of Six Sigma and many other quality initiatives that are used in a wide variety of industries. By assessing how well a stable process is performing relative to its specifications, quality practitioners are able to understand the current state of the process. They can make adjustments and reduce process variation, thereby improving quality and consistency.

Variograms in Mixed Models

Ryan Parker, Research Statistician Developer, SAS

With JMP Pro 12, we have improved fitting mixed models, with noticeable changes coming to models with spatial covariance structures.

JMP^®Graphics Tip: Alphabetic Markers

Xan Gregg, Director, Research and Development, SAS

With JMP, you can assign the marker of your choice to data points in plots to highlight your data. And you aren’t limited by the 32 built-in symbols – you can also select any character (including letters) as a marker for a scatterplot. The easiest way to set a letter as the symbol for a row is with the “Other...” item in the Marker submenu. Here’s an example using the Big Class sample data table.

Using the Relationships Among Study Procedures to Assess Data Quality

Richard C. Zink, PhD, Principal Research Statistician Developer, JMP Life Sciences

JMP® Clinical simplifies data discovery, analysis and reporting for clinical trials. With its straightforward user interface and primary reliance on graphical summaries of results, JMP Clinical allows the entire clinical trial team to explore data to identify safety or quality concerns. The upcoming Correlated Findings analysis in JMP Clinical 6.0 enables you to uncover quality issues and misconduct in clinical trials.

Probability and Multiple Choice Profiler in the Choice Platform

Melinda Thielbar, Senior Research Statistician Developer, SAS

The JMP Profiler is a powerful tool for visualizing your model. With one click, you can see what the model predicts when you change a product’s features or adjust one of your assumptions. It’s also a powerful communication tool since your audience doesn’t need a statistics background to understand the model’s message.

Estimation of a Limit of Detection

Di Michelson, Senior Analytical Training Consultant, SAS

Mark Bailey wrote an excellent article in Issue 29 of JMPer Cable detailing how to use data below a limit of detection. What do you do when you need to estimate that threshold of measurement? Analytical chemistry provides information about the concentration of an element or molecule in a substance (an analyte). Measurements of concentration have a natural bound at zero. The measurement process itself is variable, and it contains noise. Thus, measurements of a sample with known zero quantity of an analyte will result in non-zero responses. This background noise can be estimated to give a limit of detection (LOD): the upper bound on the noise of a measurement system.

JMP^® Books From SAS^® Press

Check out this upcoming title from SAS Press: Building Better Models With JMP^{® Pro} (Publication date November 2014), Jim Grayson, Sam Gardner and Mia Stephens. Explore the black box of business analytics and learn the methodology for managing and executing analytics projects.

What’s New in JMP^® Training

New courses debut at JMP® Discovery Summit 2015. Don’t miss the JMP Discovery Summit, Sept. 14 -17, in San Diego. SAS Education offers discounted JMP training to Discovery Summit attendees before and after the conference. When you register for the Summit, sign up for “Designing and Building a Complete JMP Script” or “A Case Study Approach to Data Exploration with JMP”. You can also sign up for the JMP Scripting Forum.