JMP statistical discovery software - a SAS product
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JMP (pronounced "jump") is a statistical discovery tool that helps you understand any type of data. Previously used mainly by scientists and engineers it is now used in almost every industry. JMP is highly visual and allows you to display and analyse data graphically. By using graphics, JMP lets you discover more, understand more and interact more.
Built with Your Needs in Mind
With graphically displayed data and analyses you can visualise data and see how it carries a fit. Graphs will help you discover patterns in the data and see which points don't fit the pattern. You may discover phenomena in your data that you would never have noticed had you not looked at a graph.
With results presented graphically, the statistics will become easier to understand. This encourages analyses of data and provides confidence to explore. By perceiving data both statistically and visually, you can make better informed decisions.
When you analyse and explore your data, you can also interact with it using JMP's point-and-click responsiveness. Because JMP makes it easy to interact, you explore more. The more you explore, the more discoveries you make.
JMP is built like an instrument, not a language or programming batch. You point and click rather than program or converse. You are in control. You are encouraged to try things rather than react to question-and-answer dialogs.
Some statistical software packages are strong in some techniques, such as regression, but weak in others, such as categorical methods. JMP handles all kinds of data in a consistent and unified way. It handles all combinations of continuous, ordinal and nominal data. For example, JMP treats lack-of-fit in regression the same as it does goodness-of-fit in categorical models. Most regression products don't do lack-of-fit tests, and many categorical products don't test against base models. JMP handles both lack-of-fit and tests against base models.
JMP is for the introductory user and for the expert. JMP's unified approach to statistical methods and integration of statistics with graphics gives its operation ease enough for the beginner. It rewards the beginner with analyses that are obtained with ease and are readily understood.
On the other hand, JMP also gives experts the depth they want, such as:
JMP is now also available in the JMP 13 (64-Bit Edition)
- One-way analyses that continue even after classical assumptions are left behind
- Nonlinear regression and confidence intervals that can be trusted
- Tools for reliability, Six Sigma, and many other industrial applications, including capability analysis and a large array of control charts that can receive data live from a measuring instrument
- Powerful Design of Experiments (DOE) capabilities, including classical, optimal, and supersaturated designs
- K-means, hierarchical, and normal mixtures clustering, including self-organising maps
- Exploratory modelling (sometimes known as "data mining") through classification and regression trees, and recursive partitioning
- A scripting language that allows for automation of repetitive tasks, extensions of JMP's built-in analyses, and creation of instructional simulations.
JMP 13 helps you make your own luck; discover how new analysis platforms; feature enhancements, and improvements across the entire analytics workflow- from importing
Data to sharing analysis results - helps you find the unexpected in your data.
Explore These New Features in JMP*13
Another exciting version of JMP is JMP Genomics. Used by researchers exploring the human, animal or plant genomes, JMP Genomics allows the graphical exploration of the very large genomics data sets.
See the JMP website for more details: www.jmp.com
For more information, please contact Hans de Roos:
+27 12 346 4823