JMP 13 is coming this week, and I am quite excited about this release. I’ve been using JMP 13 during the entire development cycle (about 18 months now), and I am impressed how this version has really changed the way I use JMP. For me, after using JMP 13, there
The design of experiments (DOE) capabilities of JMP are world-class. You can choose from many designs, such as custom, definitive screening, classical, space-filling, choice and covering arrays. But how do you decide which design to use? It used to be a time-consuming process to compare two designs for an experiment,
Clay Barker has been busy extending the usefulness of the Generalized Regression platform in JMP Pro, adding many new models and enhancing ease of use. Generalized Regression (or GenReg for short) debuted in JMP Pro 11 as the place to do a trio of popular penalized regression techniques: Lasso, Elastic
The purpose of screening in designed experiments is “to separate the vital few factors that have a substantial effect on the response from the trivial many that have negligible effects….The definitive screening design can reliably accomplish the task of screening even if there are a couple of second-order effects,” wrote
Building on the new features in JMP 13 for exploring unstructured text data, JMP Pro 13 enables you to do more with text data, like cluster terms and phrases and use text in predictive models. You’ll be able to answer more questions, scale to larger data and stay in flow.
From time to time, the addition of new features requires a review of how capabilities are organized and presented in JMP. Are they located where it makes the most sense and where users would expect to find them? For example, in JMP 12 there was enough new material combined with
Dashboards are such a popular way to keep an eye on important metrics and share the findings of analysis, and for years JMP users have been creating dashboards using JMP Scripting Language and tools such as Application Builder. But now in JMP 13, there’s an even easier way to make
JMP users might notice that new versions of the software often bring the ability to support new kinds of data. The ability to incorporate image data came with JMP 12, and with JMP 13 comes support for text data. In the early days of this platform’s development, we were brainstorming
MaxDiff (maximum difference scaling) is a new platform in JMP 13 that will be helpful to anyone who does consumer research. It enables a specialized type of choice model where respondents are asked to evaluate items (product attributes, …) in sets of three to five, choosing the most preferred and least
Do you ever need to visualize more than three dimensions in your graphs? If so, you likely know about parallel plots, or parallel coordinate plots. They’ve been available in JMP for a long time. In the new version of JMP, parallel plots are even easier and more fun to use