JMP statistical discovery software from SAS is the tool of choice for scientists, engineers and other data explorers in almost every industry and government sector. JMP combines powerful statistics with dynamic graphics, in memory and on the desktop. Interactive and visual, JMP reveals insights that raw tables of numbers or static graphs tend to hide.
Because everything is linked – the graphics, statistics and data – JMP encourages you to dig deeper and ask more questions, improving your chance of making breakthrough discoveries in your data. With JMP, analyses unfold, driven by what the data reveals at each step. You can explore your data without leaving the analysis flow or having to rerun commands as new questions arise.
JMP brings your data analysis to a whole new level, letting you tackle routine and difficult statistical problems more easily and communicate your findings more effectively.
JMP statistical discovery software from SAS enables you to make breakthrough discoveries by dynamically linking graphics and powerful statistics.
Many organizations rely on “A-B testing” for experimental design, but testing one situation against another with many factors in flux is a very slow way to learn about your business.
In contrast, design of experiments (DOE) in JMP offers a proven and practical approach for exploring and exploiting the multifactor opportunities that exist in almost all real-world situations. Using multifactor experiments, you learn more quickly, at minimal cost, by teasing out not just the effect of an individual factor, but also the combined impact of two or more factors. JMP offers leading-edge capabilities for design of experiments, so you can design the best experiments to answer specific questions. JMP also offers a rich set of analyses tailored to your design in a form you can easily use.
Instead of fitting your problem to a textbook design, you fit the design to your problem with the budget you have. The unique Custom Designer constructs an optimal design for your problem, taking into account specific conditions such as time, budget and other experimental constraints.
Once you have completed your sophisticated analyses, employing basic tools for visual analysis is often the best way to communicate results and motivate action. The interactivity of JMP gives you the tools to share the meaning in graphs and not just the graphs themselves.
The market demands continual improvement, which is why you strive to accelerate time to market, protect your brand by minimizing customer complaints, and deliver products and services that consistently meet or exceed customer expectations. JMP has the necessary tools to be at the heart of your quality program, providing a wide range of relevant graphical and statistical capabilities.
The JMP® Solution
It’s easier to work productively if you can configure your software to work the way you think. Consistent settings, graph output and even color palettes mean fewer steps to understanding data. JMP gives you a comprehensive set of preferences that enable you to control fonts, graphic options and detailed settings within platforms. It’s analysis the way you like it. You can even choose to display only those analytic tools and menus you use routinely. In fact, you can customize every aspect of JMP, including:
- Graph axis settings, styles, graphs and colors.
- Statistical and graphical elements presented in a JMP report.
- Import settings that can be predefined to take in new data in a form you can use immediately.
- Your environment for scripting and application development.
As a member of the SAS family, JMP offers a seamless interface to the unparalleled capabilities of SAS. The deep analytics, reporting and data management capabilities of SAS extend capabilities of JMP desktop software to the server and beyond. You can also use JMP with other analytic tools, including a full interface to the power of MATLAB, complete calling interface to DLLs and the rich set of specialized libraries in R. JMP makes it easy to reach out to these resources and bring back results for dynamic data visualization and analysis. Or you can seamlessly integrate an algorithm or function into the JMP workflow, making SAS, MATLAB or R feel like part of JMP.
Minimize data drudgery
How much time do you spend preparing your data for analysis? For many data analysts this is a constant chore. JMP has long respected this fact and worked to make data preparation easier, faster and more reliable.
No matter what your data cleaning tasks, JMP automates the process. What is hard or even impossible in other software is easy in JMP. And even if you can’t clean your data directly, JMP includes methods to minimize the impact of data problems on your analysis, often eliminating the need (and effort required) to make your data pristine.
Once your data resides in a JMP table, you can take advantage of rich reshaping and restructuring tools, merge all of your data into a single file, and easily perform intelligent and interactive table joins.
Before you analyze your data, you should check to make sure it is clean, that the values are consistent and encoded well. JMP offers many ways to do this. One of the best is with the Distribution platform. If you spot outliers, simply grab them and they are selected in the table, thanks to dynamic linking in JMP.
Having a visual interface to your data is a powerful advantage of JMP. You will soon wonder how much you were missing before you were able to immediately grab what you see in your data.
When many different individuals enter categories, naming can become inconsistent. To accurately tabulate the categories and use them for prediction, they must match up consistently. JMP has a Recode utility to make consolidation of categories easy rather than time-consuming. You can select a set of categories and choose which of them to make representative of the group. You can also tell JMP to automatically consolidate categories that are very similar to each other. This can be an incredible time saver, especially when there are hundreds or thousands of unique entries.
Other tools for data cleanup in JMP include:
- Screening for outliers.
- Screening for entry errors, error codes or missing values/missing value codes you might not have accounted for in your data.
- Creating formula columns or derived variables; ratio columns or response transformations.
- Data property cleanup.
- Binning continuous data into discrete categories.
- Splitting strings of delimited text into multiple columns.
- Making indicator variables.
- Standardizing attributes across many similar-type columns.
Make compelling data visualizations
Spreadsheets don’t easily reveal patterns and trends in data sets, yet seeing patterns helps you make discoveries. JMP provides rich and dynamic visualization tools, making statistical discovery easier and more effective, leading to innovation.
JMP frees you from the narrow path so you can explore your data dynamically and allow it to tell you what is interesting. Move through your data quickly and with agility until you find the visualization that best communicates the story in your data.
Graph Builder is the best way to begin exploring and graphing your data. Interactively build simple or complex graphical displays just by dragging and dropping. Simply drag the variables into position, choose the graph element from an icon palette, and customize the display to get your final, publication-quality result. Graph Builder always gives you options that make sense for your situation.
You can also add background maps to all relevant JMP graphs using high-quality, built-in geographic images, or plot data on street-level maps that include cities, roads and bodies of water. With Bubble Plot, you can create animated data movies, showing changes in many dimensions over time.
Dynamic linking perhaps best illustrates the magic of JMP. You can select elements from any graph and instantly see the selection propagate to multiple views, yielding insights that other software simply can’t reveal.
Perform basic data analysis
Employing basic tools for visual analysis is often the best way to communicate results and motivate action in an organization. And frequently, your first step in a statistical data inquiry consists of investigating variables one at a time, a process known as univariate analysis. In JMP, once you’ve identified the columns that interest you, the Distribution platform automatically provides graphs and statistics based on the variable’s defined modeling type.
Quickly get histograms, summary statistics, box plots and quantiles for continuous data, capability analysis, distribution fitting and frequencies for nominal or ordinal values.
Key capabilities in JMP for basic statistical analysis include:
- Histograms, box plots.
- Descriptive statistics.
- One- and two-sample t-tests, ANOVA, regression, nonparametric tests.
- Distribution fitting.
- Fitting splines and curves to data.
- Statistical calculators and simulators; power and sample size calculation.
Group and filter data with ease
In any business, the quicker you can learn and adapt to ever-changing customer needs, the quicker you can get ahead of your competition. To accelerate this learning cycle, you need to be able to notice patterns in your data, focus on the most important, and act quickly. You can’t waste time generating a stack of reports to wade through, or worse, writing custom code and waiting for output before acting.
JMP brings a radically different approach to the daily task of slicing and dicing data. Its grouping and filtering paradigm allows for instant, in-memory recasting of report output. Imagine how quickly you can focus on interesting areas when you can update reports on the fly just by clicking through levels of a categorical variable. With one click, you can even switch the analysis focus to a new metric entirely.
Grouping and filtering tools in JMP include:
- Local and global data filters for focusing on specific parts of your data table, with or without conditional statements. The ability to save favorite filter settings brings efficiency to routine filtering tasks.
- Easy-to-define row markers, colors and labels that enrich graphical reports and data tables.
- Column Switcher for swapping variables within a graphical or statistical report. Stepping through variables manually or by animation allows you to spot patterns and anomalies when you have hundreds of variables.
- Easy creation of By variables in many analysis platforms generates multiple copies of the same analysis; multiple subset analysis in a single click.
- Transforms for generating derived variables on the fly. Stay in the flow while you are analyzing data and create many statistical or mathematical transformed columns of your data with a single click.
- Graph filtering. Use a graph to filter another graph.
Expedite data access
Your data comes in many forms. Fortunately for you, JMP is hungry for data.
Easily read from Microsoft Excel using the Excel Import Wizard, from text files using the Text Import Wizard, and pull data directly from ODBC-compliant databases using the interactive Query Builder. Whatever the format, JMP is ready.
Databases allow organizations to catalog massive amounts of data and information, but this means that the data you need for analysis is often scattered across multiple tables. Joining those tables to assemble the data you need can make for significant work and require you to learn not only the details of the data tables, but also how to use SQL or other tools to join them.
Enter Query Builder, the interactive JMP platform that requires no SQL coding. Using this JMP platform, you specify only the primary table and one or more secondary tables, and Query Builder automatically matches foreign keys in the primary table to primary keys in the secondary tables. So joining is no longer a laborious process – it becomes automatic.
Combined with automatic matching, Query Builder has everything you need to build your simple or complex query. Now, you can do it all with JMP.
Does your data live in spreadsheets? With the JMP add-in for Microsoft Excel, you can easily move data from Excel into JMP or bring the power of the Profiler for JMP to your spreadsheet models, enhancing the data with the advantages of JMP visualization.
JMP also lets you import and sample data from other sources, including:
- Many types of flat sources (e.g., text files, HTML files, SPSS data files, Minitab portable worksheet files).
- Web pages (HTML tables).
SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions delivered within an integrated framework, SAS helps customers at more than 50,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW®.
JMP® software is published by SAS Institute Inc. (www.sas.com).