Preface

JMP is statistical discovery software. JMP helps you explore data, fit models, discover patterns, and discover points that don’t fit patterns. This book is a guide to statistics using JMP.

The Software

As statistical discovery software, JMP emphasizes working interactively with data and graphics in a progressive structure to make discoveries.

●   With graphics, you are more likely to make discoveries. You are also more likely to understand the results.

●   With interactivity, you are encouraged to dig deeper and try out more things that might improve your chances of discovering something important. With interactivity, one analysis leads to a refinement, and one discovery leads to another discovery.

●   With a progressive structure, you build a context that maintains a live analysis. You don’t have to redo analyses and plots to make changes in them, so details come to attention at the right time.

The purpose of JMP software is to create a virtual workplace. The software has facilities and platforms where the tools are located and the work is performed. JMP provides the workplace that we think is best for the job of analyzing data. With the right software workplace, researchers embrace computers and statistics, rather than avoid them.

JMP aims to present a graph with every statistic. You should always see the analysis in both ways, with statistical text and graphics, without having to ask for it. The text and graphs stay together.

JMP is controlled largely through point-and-click mouse manipulation. If you place the pointer over a point, JMP identifies it. If you click on a point in a plot, JMP highlights the point in the plot and highlights the point in the data table. In fact, JMP highlights the point everywhere it is represented.

JMP has a progressive organization. You begin with a simple report at the top, and as you analyze, more and more depth is revealed. The analysis is alive, and as you dig deeper into the data, more and more options are offered according to the context of the analysis.

In JMP, completeness is not measured by the “feature count,” but by the range of possible applications, and the orthogonality of the tools. In JMP, you get a feeling of being in more control despite your having less awareness of the control surface. You also get a feeling that statistics is an orderly discipline that makes sense, rather than an unorganized collection of methods.

A statistical software application is often the point of entry into the practice of statistics. JMP strives to offer fulfillment rather than frustration, empowerment rather than intimidation.

If you give someone a large truck, they will find someone to drive it for them. But if you give them a sports car, they will learn to drive it themselves. We believe that statistics can be interesting and reachable so that people will want to drive that vehicle.

How to Get JMP

There are several ways to get JMP:

●   JMP is available through department or campus licenses at most colleges and universities and through site licenses in many organizations. See your software IT administrator for availability and download information.

●   Individual copies of JMP for academic use are also available from http://onthehub.com/jmp. If you would like more information about academic licensing or would like to request an evaluation copy of JMP for classroom use, email [email protected].

●   If you do not qualify for an academic license, a trial version of JMP is available at http://jmp.com/trial. Read license information at http://jmp.com/buy.

JMP Start Statistics, Sixth Edition

JMP Start Statistics has been updated and revised to feature JMP 13. Major enhancements have been made to JMP since the fifth edition, which was based on JMP 10. The new enhancements include DOE (Design Evaluation, new Custom Design options, and Definitive Screening designs), analysis and modeling (Generalized Regression, Partition enhancements, Model Comparison, and Formula Depot), data preparation (handling missing values and outliers, and model validation), and graphics (continued development of the interactive Graph Builder), most of which are covered in this book. In addition, the menus have been restructured, and we’ve added functionality for getting data into JMP (Query Builder) and sharing results (saving as Microsoft PowerPoint, saving as HTML, and creating interactive web reports).

JMP 13 also continues our focus on enhancing the user experience, with new daily Tips of the Day and expanded documentation.

We include discussion of many of these new features throughout this text.

SAS

SAS, or the SAS System, is an integrated statistical software system used by universities, research institutions, and industries across the globe. JMP Statistical Discovery Software is desktop software from SAS that runs natively on Mac and Windows. JMP was originally designed as a personal analysis tool for engineers and scientists, but is now used in a variety of applications and industries worldwide.

JMP versus JMP Pro

JMP was first released by SAS in 1989 to run on a Macintosh operating system, and became available on Windows in the early 1990s. Since then, JMP has grown into a family of products, each designed to meet particular needs.

In this book we use JMP Pro, which includes advanced tools for analytics and predictive modeling. However, JMP Pro is not required to take full advantage of the methods covered. Unless otherwise specified, the features that we discuss are available in both JMP and JMP Pro.

This Book

Software Manual and Statistics Text

This book is a mix of software manual and statistics text. It is designed to be a complete and orderly introduction to analyzing data. It is a teaching text, but is especially useful when used in conjunction with a standard statistical textbook.

Not Just the Basics

A few of the techniques in this book are not found in most introductory statistics courses, but are accessible in basic form using JMP. These techniques include logistic regression, correspondence analysis, principal components with biplots, leverage plots, and density estimation. All these techniques are used in the service of understanding other, more basic methods. Where appropriate, supplemental material is labeled as “Special Topics” so that it is recognized as optional material.

JMP also includes several advanced methods not covered in this book, such as nonlinear regression, multivariate analysis of variance, tools for predictive modeling and data mining, consumer research methods, text mining, and some advanced design of experiments capabilities. If you are planning to use these features extensively, it is recommended that you refer to the Help system or the JMP documentation for the professional version of JMP.

Examples Both Real and Simulated

Most examples are real-world applications. A few simulations are included too, so that the difference between a true value and its estimate can be discussed, along with the variability in the estimates. Some examples are unusual and are calculated to emphasize an important concept. The data for the examples are installed with JMP, with step-by-step instructions in the text. The same data are also available on the Internet at http://support.sas.com/stephens. JMP can also import data from files that are distributed with other textbooks. See Chapter 3, “Data Tables, Reports, and Scripts,” for details about importing various types of data.

Acknowledgments

Thank you to the JMP testers as well as the contributors and reviewers of earlier versions of JMP Start Statistics: Bradley Jones, Chris Gotwalt, Lou Valente, Tom Donnelly, Michael Benson, Avignor Cahaner, Howard Yetter, David Ikle, Robert Stine, Andy Mauromoustkos, Al Best, Jacques Goupy, and Chris Olsen for contributions to earlier versions of the book. Special thanks to Curt Hinrichs for invaluable support to the JMP Start Statistics project.