New in JMP 15 and JMP Pro 15 (PDF)
Scientists, engineers and other data explorers need their data to be interactive and accessible—from making discoveries themselves and sharing these insights with others to digging into the analyses of their colleagues. The latest version of JMP data analysis software has new ways to understand data more fully with fewer clicks and enhanced options for sharing findings with others. Those who use JMP Pro 15 have even more modeling tools to take their analyses to the next level—no matter what form the data comes in.
The new features in data tables and graphs, collectively called informative decoration, offer even greater understanding in fewer clicks. Histograms are now presented above each column, and function with the same interactivity of histograms throughout JMP. Histograms are also provided in local data filters, to better inform your filtering decisions. Finally, graphlets, textlets and gridlets provide context while keeping you in the flow of the analysis. Graphlets are supported in the Principal Components, Process Screening and Multivariate Control Charts platforms.
For many users, each analysis begins with importing any of a variety of file types. Data lives in many places, and JMP helps you spend more time analyzing data, and less time importing it. In JMP 15, wizards have been added to process data in XML, JSON and .pdf formats. With a few clicks, you can specify import options and bring these files into JMP.
The .pdf import wizard identifies tables in .pdf files, streamlining the process of importing .pdf content into JMP. You can combine all tables into a single table, create tables individually or combine select tables.
The built-in XML and JSON importers can handle nested and complex files.
The primary graphing platform in JMP keeps improving. Enhanced Graph Builder in JMP 15 means new graphs, including time-series forecasts, more customization options for existing graphs and the ability to drill down for more detail using graphlets. Graph Builder has many other enhancements in JMP 15, including:
Data cleanup remains the most challenging and time-consuming part of the analytic workflow. JMP 15 simplifies the process by making it easier to recode column names, implement custom sort orderings and automate the recode process.
Virtual Joins have also been improved, allowing a single column to be used both as a key and a reference and new hover tips to determine a linked column's source table. Additionally with virtual joins in JMP 15, when one of a linked set of tables is opened, the others can be automatically opened as well.
The DOE platform in JMP is world-class, better enabling users to solve challenging problems in a wide variety of real-world settings. In JMP 15, numerous improvements to the DOE features have been added, enabling users to create better designs more quickly, and analyze them more easily.
Group Orthogonal Supersaturated Design (GO SSD) is a new platform to create and analyze supersaturated designs. In a GO SSD, factors are placed into groups: factors in the same group are correlated but they are uncorrelated with any factors in a different group. Unlike other supersaturated designs, JMP can treat the first group of factors (containing unbalanced columns) as unused factors.
Also, in JMP Pro 15 the custom designer can now be used to design functional response DOEs, where at least one response of interest is not a scalar, but a function.
Explore Patterns is a screening utility that investigates data integrity and can help you identify unexpected patterns in data. The platform looks for duplicate series of values, linear relationships between columns across groups of rows, properties about the formatted values and certain distributional properties. Generally, Explore Patterns is most useful when the values are fairly precise, so that matches are less likely to exist through coincidence.
Scientists and engineers are dealing with more and more data streamed from device-based sensors or batch process monitors. Hundreds or thousands of such data streams can create a large volume of data, very quickly, posing a unique set of challenges. No matter what your industry, common difficulties exist with this type of data: simplifying and cleaning up messy data, removing outliers and building models that characterize an underlying function or relate a continuous data stream to measures of performance, such as yield, defect rate or product quality.
JMP Pro 14 introduced FDE, a powerful platform for working with functional data. JMP Pro 15 adds workflow improvements that let users bypass intermediate table creation reshaping, and joins, especially for functional DOEs. The custom designer in JMP Pro 15 allows users to specify a functional response, making the subsequent workflow more convenient and less error-prone. Additionally, with FDE in JMP Pro 15 you can:
The new Structural Equation Modeling platform in JMP 15 lets you quickly specify, edit, run and compare SEM models using an easy-to-use interface. Structural Equation Modeling is a framework that allows you to specify hypothesized relationships among variables (both observed and unobserved) and test the degree to which these hypotheses seem reasonable, given the data. SEM can be used by anyone who is using standard modeling techniques but needs more control and flexibility in the model specification process.
SEM in JMP Pro 15 is versatile and provides options for modeling simple or multiple regression relationships as well as comparing a set of hypothetical models to decide which model is most reasonable.
With JMP 15, you'll find it easier to build and evaluate models. Multiple contour profilers can be viewed simultaneously. In JMP Pro, the Make Validation Column utility offers more control and an improved interface, and Generalized Regression offers built-in model comparison, improved one-click relaunch options and the ability to change distributions without having to relaunch.
Univariate control charts are unable to account for correlation or functional relationships among multiple parameters. When such relationships exist, standard univariate charts will not accurately depict process health. JMP 15 provides control charts that support these relationships, providing a better understanding of actual process performance. The new Model-Driven Multivariate Control Chart platform in JMP 15 offers several benefits:
JMP 15 makes it easier for novice scripters to automate their work, allowing them to capture, in a single click, the JSL needed to reproduce common workflows. Also, the new option to copy a table script allows you to capture the table script, without the data itself. Table scripts and all column properties (including formulas) are included.
When you just need to get the JSL for a column (or a few), you can use the new Copy Columns and Paste Columns features in JMP 15. This is especially handy when the columns have properties that require lots of JSL—as value orders, value labels, spec limits, date-time formats and formulas do.
You can also copy Where Clauses, which avoids the need to script complicated conditional row selections (“Where clauses”) and lets you easily capture the JSL needed to make the selection.
In JMP 15, interactive HTML reports have improved support for within-report profilers. Released at the same time as JMP 15, JMP Live is a web-based collaborative analytics platform for JMP. With JMP Live, users can share discoveries using a simple publishing process that fits seamlessly into the JMP analysis workflow. Publish data, dashboards or reports to JMP Live, and have colleagues view the findings—even if they don’t have a JMP license.
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