JMP

What is JMP?

JMP, the data analysis software for Mac and Windows, combines the strength of interactive visualization with powerful statistics. Importing and processing data is made easy through its drag-and-drop interface, dynamically linked graphs, libraries of advanced analytic functionality, scripting language, and ways of sharing findings with others. This allows users to dig deeply into their data with greater ease and speed. Originally developed in the 1980s to capture the new value in GUI for personal computers, JMP remains dedicated to adding cutting-edge statistical methods and special analysis techniques from a variety of industries to the software's functionality with each release. The organization's founder, John Sall, still serves as Chief Architect JMP's advanced predictive modeling capabilities utilize modern techniques like regression, neural networks, and decision trees, enabling users to build better models. Users can effectively segment, model, analyze, and experiment with quantitative and qualitative data to direct decisions with objective insights. The interactive graphs in JMP represent a linked interface, allowing for better decision support with the frictionless presentation of the source of truth at the point of decision JMP is the data analysis tool of choice for hundreds of thousands of scientists, engineers, and other data explorers worldwide. Users leverage the powerful statistical and analytic capabilities in JMP to discover the unexpected, tackling both routine and difficult statistical problems. From easily accessing data from various sources to using quick, reliable data preparation tools and performing choice statistical analyses, JMP enables users to get the most out of their data in any situation. The data visualization capabilities in JMP allow users to move effortlessly from discovery to sharing, telling the story of their findings with interactive dashboards and web visualizations

Highlights

• Drag-and-drop interface for easy data importing and processing
• Dynamically linked graphs and interactive data visualization capabilities
• Libraries of advanced analytic functionality, including predictive modeling techniques
• Scripting language and ways of sharing findings with others
• Cutting-edge statistical methods and special analysis techniques added with each release
• Objective insights from segmentation, modeling, analysis, and experimentation of quantitative and qualitative data