![]() ![]() This book is part of the SAS Press program. With today’s emphasis on business intelligence, business analytics, and predictive analytics, this second edition is invaluable to anyone who needs to expand his or her knowledge of statistics and to apply real-world, problem-solving analysis. Using JMP 13 and JMP 13 Pro, this book offers the following new and enhanced features in an example-driven format: Second, it teaches you how to interpret the results and then, step-by-step, how and where to perform and evaluate the analysis in JMP. Going beyond the theoretical foundation, this book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis.įirst, this book teaches you to recognize when it is appropriate to use a tool, what variables and data are required, and what the results might be. For more details, visit for students in undergraduate and graduate statistics courses, as well as for the practitioner who wants to make better decisions from data and models, this updated and expanded second edition of Fundamentals of Predictive Analytics with JMP(R) bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Single-user licences, as well as short-term academic licences for qualified students and faculty, are also available. Sixty-four-bit Windows and Linux versions will be available later this year.Ĭorporate and academic licences are available for JMP 7 by annual subscription. It runs on Macintosh, Linux and Windows systems, including Windows Vista. JMP 7 processes up to 2 billion variables and an unlimited number of records to handle any real-world problem. "Everything in JMP is active on the surface. "JMP 7 brings your data to you in a way that is close, personal and allows direct data manipulation," said Goran Dragosavac, product manager for Analytical Intelligence at SAS SA. When a colleague opens the project, JMP restores the entire desktop so discovery can be picked up where it was left off. An easy-to-use new project feature lets users drag data tables, journals, scripts, files and even e-mails into the project to facilitate collaboration. JMP graphs and analyses can be stored with the data, replayed and edited. JMP 7 automatically updates graphs and reports immediately to display query results. Graphic data filters select, exclude, hide or otherwise query data to answer "what if" questions based on any combination of factors. SAS programmers can now generate results as interactive JMP graphs and reports that can be shared throughout the organisation to offer insights that improve decision-making.īubble plots, 3D scatter plots and other new features let novice and experienced JMP users alike explore data and animate up to seven variables. This first release of JMP, as a desktop client to the SAS Enterprise Intelligence Platform enables even users without programming skills to access and explore SAS data interactively. Hundreds of thousands of JMP users worldwide, plus SAS users new to JMP, will be able to delve deep into their data to understand their businesses inside and out. JMP 7 integrates completely with SAS to offer a unique, graphical environment for exploring huge amounts of SAS data and developing SAS code on the desktop. Graphical data querying, an enhanced script editor and project collaboration tools make data discovery more accessible throughout the organisation. Traditionally used by scientists and engineers, JMP 7 now appeals equally to business users, who can replace static charts with motion-enabled, interactive plots that uncover hidden trends and predict the future. Try to right-click in the graph area or on the axes or double-click the legend and explore the options available to you. ![]() SAS, the leader in business intelligence, brings data visualisation and analytics to a new level with the launch of JMP 7 statistical discovery software.ĭynamic new graphical capabilities, the ability to manage virtually unlimited volumes of data and seamless integration with powerful SAS Analytics highlight a long list of enhancements. ![]()
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