Building Better Models with JMP^® Pro provides a clean and concise introduction to the topic of modeling using JMP Pro. The book is comprehensive, covering a wide array of modeling techniques. Part 3 of the book covers multiple linear regression, logistic regression, decision trees, and neural networks. Most of this material requires only JMP software. Part 4 of the book covers more advanced methods that require JMP Pro, including JMP's bootstrap forest and boosted tree methods, boosted neural nets, penalized (generalized) regression methods, cross validation, and model comparison techniques. Data sets accompany the book so that a reader can easily follow along.

What sets the book apart, though, is its elegant structure. Each modeling chapter captures the reader's attention with three short sections: A section where the topic is mentioned "In the News", a section listing typical business problems where the technique applies, and a section showcasing the expected outcome of the modeling technique. For those readers who want a glimpse of the mechanics behind a technique, a section called "Looking Inside the Black Box" discusses the methodology behind the algorithm, providing appropriate statistical detail. An understanding of the modeling technique is developed through examples, using JMP Pro and the data tables provided with the book. For those who want to further their skills and knowledge, the authors provide exercises based on the data tables, as well as a list of references.

No previous knowledge of JMP software is required, as the authors provide a thorough introduction to the software's basic structure in Chapter 3. Plots and techniques that are frequently used in data exploration as a preparation for modeling are discussed and illustrated using the data tables. Chapter 10, the book's final chapter, draws together the tools discussed in the prior chapters in three comprehensive case studies.

The book strikes an appealing balance between showing the reader how to use JMP Pro to obtain results and providing the reader with a background understanding of the techniques being used. It is an excellent supplement for an introductory course on analytics. It is equally appropriate for self-learning. This book will draw you in. It will demonstrate the potential and the power of analytics and furnish you with the tools to access that potential.

Marie Gaudard
Professor of Statistics Emerita
University of New Hampshire

Building Better Models with JMP^® Pro will undoubtedly be the reference book for all those who, from student to professional, need to understand what they do when they practice business analytics with JMP.

In chapters dedicated to the presentation of the four main modeling methods (linear regression, logistic regression, decision trees, and neural networks), the authors take the time to show a little "what's under the hood" by presenting the algorithms at work. The interest of the presentation is also to encourage readers to "get their hands dirty" by practicing modeling with JMP on sufficiently complex cases. One can then see all the interest of the JMP Profiler that allows better understanding of the different candidate models, and the interest of the Models Comparison platform.

Finally, the authors rightly insist in the last two chapters on cross validation, and some advanced methods where JMP (JMP Pro) reveals its processing power, well-illustrated in the final case studies.

Yves Gueniffey
Professor of Statistics and Data Analysis
Ecole des Mines de Nancy, France

I have been using JMP for several years and the package is outstanding; however, what was missing was a book like this one. The authors have written a highly readable and comprehensive textbook that covers all of the important topics of Data Mining. They provide great coverage of the fundamental concepts behind each technique but they also explain how JMP is used to support the Data Mining process. As a result of this book, I have completely revised my Data Mining class and I am confident that the students will respond favorably to the textbook and the resulting changes to my course. I cannot wait to use this book next semester!

Robert Nydick, Ph.D.
Villanova University
Department of Management and Operations

Building Better Models with JMP^® Pro by Jim Grayson, Mia L. Stephens and Sam Gardner offers a great introduction to statistical analysis and predictive modeling. It provides a clear and practical approach for students and professionals alike who are interested in learning how to perform data analysis for business application using JMP, an intuitive, easy-to-use software platform. I highly recommend it!

Matthew J. Liberatore, PhD
Villanova School of Business
Villanova University