SAS JMP Statistical Discovery Pro 14.3.0
SAS JMP Statistical Discovery Pro 14.3.0 | 1.8 Gb
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The 14 version of JMP statistical discovery software from SAS provides users new opportunities for faster, deeper insights across the entire analytics workflow: new ways to connect to data sources, new tools to streamline data cleanup, and more options for data visualization and designed experiments. And with JMP Pro 14, the advanced analytics version of JMP, users have new tools for predictive modeling. Both JMP 14 and JMP Pro 14 are released today.
JMP 14 highlights
- JMP Projects to organize files and manage multiple open windows with a drag-and-drop tabbed interface.
- New Recode tools and automated routines to get data ready for analysis more quickly.
- Multiple file import to quickly and accurately combine hundreds - or even thousands - of files into one JMP data table.
- Graph Builder improvements including the new packed bars chart, which combines elements from treemaps and Pareto plots; finer graph customization; and easy creation of custom error bars.
- Interface to Python to connect to Python, send data, execute Python code and return data to JMP for analysis or visualization.
- HTTP Request to communicate with external web servers through JSL. Addition of JSON parsing functions makes it much easier to get web data into JMP.
- A-optimality criterion in Custom Design for putting different emphasis on groups of parameters through weighting.
- New Multiple Factor Analysis for sensory analysis to help identify groupings of similar products and detect outliers that can skew results.
- Drift detection, Goal Plot, three-way chart calculations and numerous UI improvements in Process Screening platform.
- Bayesian Inference for Fit Life by X.
JMP Pro 14 highlights
- New Functional Data Explorer to understand, clean, align and build models from sensor streams or batch process data.
- Discriminant analysis in Text Explorer to dig deeper into text.
- Validation column in Text Explorer for use in a predictive modeling workflow.
- More distributions, including more censoring, and multinomial response in Generalized Regression to build models for diverse data.
- Ability to publish recode columns to the Formula Depot.
- Improvements to K-NN and Na�ve Bayes. K-NN adds model selection, and both add profilers.
Release Notes for JMP 14.3 - Date: March 2019
JMP 14.3 is a general maintenance release that contains enhancements and bug fixes. Applying this maintenance release is recommended for all users.
New Features
- On Windows, the libcurl DLL files have been upgraded to version 7.63.0.
- The Using JMP documentation PDF file is available in Korean.
General Improvements
- When closing a custom window that contains a platform and an On Close() function that closes a data table, JMP no longer closes abruptly.
- On Windows, the Oracle JRE has been removed from the installer. In JMP 15, the Azul JRE will be included.
- Dragging multiple response columns on the Structured tab in Categorical no longer causes JMP to close abruptly.
- In REML, the DenDF is now correct when the response is of great magnitude.
- In MaxDiff, the bar charts reflect the correct marginal probability values.
JMP is the data analysis tool of choice for hundreds of thousands of scientists, engineers and other data explorers worldwide. Users leverage powerful statistical and analytic capabilities in JMP to discover the unexpected.
As the pro version of JMP statistical discovery software, JMP Pro goes to the next level by offering all the capabilities of JMP plus advanced features for more sophisticated analysis including predictive modeling and cross-validation techniques. Users can harness the power and speed of the supercomputer on their desk to explore and understand data in an easy-to-use interface.
JMP 14 Tutorial - Tabulate
SAS created JMP in 1989 to empower scientists and engineers to explore and analyze data visually. Since then, JMP has grown from a single product into a family of statistical discovery tools, each one tailored to meet specific needs. John Sall, SAS co-founder and Executive Vice President, heads the JMP business unit.
SAS is the leader in analytics. Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS gives you THE POWER TO KNOW.
Product: SAS JMP Statistical Discovery
Version: Pro 14.3.0
Supported Architectures: 32bit / 64bit
http://www.jmp.com Language: multilanguage
System Requirements: PC *
Supported Operating Systems: *
Size: 1.8 Gb
Supported Operating Systems:
Windows 10 (except Windows 10 S edition)
Windows 8.1 (except the RT edition)
Windows 7 SP1 (except Windows 7 Starter and Windows 7 Home Basic editions)
Windows Server 2008 R2 SP1 (x64)
Windows Server 2012 (x64)
Windows Server 2012 R2 (x64)
Windows Server 2016 (x64)
Notes: JMP server license needed for use on Windows server operating systems.
JMP shrinkwrap license is only available as a 32-bit version.
CPU: 32-bit: x86 class processor; 64-bit *: x64 processor
RAM **: 32-bit systems: 1 GB minimum, 2 GB or more recommended; 64-bit systems*: 4 GB or more recommended
Drive Space: 1 GB (plus up to 250 MB for additional software below, if not already installed)
Browser: Internet Explorer 11.0 or greater, newer browsers highly recommended for viewing JMP Help and JMP Interactive HTML output
Recommended Display: True (32-bit or more) color with resolution of 1024x768 or greater; video card with hardware accelerated 2D and 3D drivers recommended
Database: UNICODE compliant ODBC 3.5 or higher (required only if connecting to database)***
Additional Required Software (included with JMP installer):
Microsoft .NET Framework 4.6.1
Microsoft Visual C++ 2017 Redistributable
Oracle JRE 1.8: Minimum JRE of version 1.7 needed to connect JMP with SAS software. The bitness of the JRE installed needs to match the bitness of JMP installed
JMP add-in for Excel requires one of the following:
Excel 2010
Excel 2013
Excel 2016
Other Compatible Software (not required):
SAS 9.1.3 SP4
SAS 9.2
SAS 9.3
SAS 9.4
R open-source statistical software releases 2.9.1 or higher
MATLAB R2012a (version 7.14.0) or higher
Python 3.6.1
* 64-Bit versions of JMP and JMP Pro only.
** JMP is an in-memory analysis tool. Your memory requirements will depend on the amount of data being analyzed.
**** JMP does not support the FileMaker Pro database on Windows.
visualization and designed experiments.
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