Practical Data Analysis with JMP, Third Edition. Robert Carver

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Practical Data Analysis with JMP, Third Edition - Robert Carver

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I have added the Partition Platform to the discussion of variable selection. The Fit Curve platform also makes its first appearance, as do temporary variable transformations.

      ● For JMP Pro users, there is a brief treatment of the Formula Depot to facilitate comparison of models.

      ● In Chapter 21 on Design of Experiments, we meet Definitive Screening Designs.

      ● In Chapter 22, Variability Charts have been added.

      ● Simulators and calculators previously supplied as JSL scripts in earlier editions have been bundled among JMP’s teaching demonstrations in the Help system. The text now reflects this very useful change.

      Is This Book for You?

      Intended Audience

      This book is intended to supplement an introductory college-level statistics course with real investigations of some important and engaging problems. Each chapter presents a set of self-paced exercises to help students learn the skills of quantitative reasoning by performing the types of analyses that typically form the core of a first course in applied statistics. Students can learn and practice the software skills outside of class. Instructors can devote class time to statistics and statistical reasoning, rather than to rudimentary software instruction. Both students and teachers can direct their energies to the practice of data analysis in ways that inform students’ understanding of the world through investigations of problems that matter in various fields of study.

      Though written with undergraduate and beginning graduate students in mind, some practitioners might find the book helpful on the job and are well-advised to read the book selectively to address current tasks or projects. Chapters 1 and 2 form a good starting point before reading later sections. Appendix B (online for this edition) covers several data management topics that might be helpful for readers who undertake projects involving disparate data sources.

      Prerequisites

      No prior statistical knowledge is presumed. A basic grounding in algebra and some familiarity with the Mac OS or Windows environment are all you need in advance. An open, curious mind is also helpful.

      A Message for Instructors

      I assume that most teachers view class time as a scarce resource. One of my goals in writing this book was to strive for clarity throughout so that students can be expected to work through the book on their own and learn through their encounters with the examples and exercises. This book may be especially welcome for instructors using an inverted, or flipped, classroom approach.

      Instructors might selectively use exercises as in-class demonstrations or group activities, interspersing instruction or discussion with computer work. More often, the chapters and scenarios can serve as homework exercises or assignments, either to prepare for other work, to acquire skills and understanding, or to demonstrate progress and mastery. Finally, some instructors might want to assign a chapter in connection with an independent analysis project. Several of the data tables contain additional variables that are not used within chapters. These variables might form the basis for original analyses or explorations.

      The bibliography may also aid instructors seeking additional data sources or background material for exercises and assignments. Tips for classroom use of JMP are also available at the book’s website, accessible through the author’s page at support.sas.com/carver.

      A Message for Students

      Remember that the primary goal of this book is to help you understand the concepts and techniques of statistical analysis. JMP provides an ideal software environment to do just that. Naturally, each chapter is “about” the software and at times you will find yourself focusing on the details of a JMP analysis platform and its options. If you become entangled in the specifics of a problem, step back and try to refocus on the main statistical ideas rather than software issues.

      This book should augment, but not replace, your primary textbook or your classroom time. To get the maximum benefit from the book, work mindfully and carefully. Read through a chapter before you sit down at the computer. Each chapter will require approximately 30 minutes of computer time; work at your own pace and take your time. Remember that variability is omnipresent, so expect that the time you need to complete a chapter may be more or less than 30 minutes.

      The Application Scenarios at the end of each chapter are designed to reinforce and extend what you have learned in the chapter. The questions in this section are designed to challenge you. Sometimes, it is obvious how to proceed with your analysis; sometimes, you will need to think a bit before you issue your first command. The idea is to engage in statistical thinking, integrating what you have learned throughout your course. There is much more to data analysis than finding a numerical answer, and these questions provide an opportunity to do realistic analysis. Because the examples use real data, don’t expect to find neat “pat” results; computations won’t typically come out to nice round numbers.

      JMP is a large program designed for diverse user needs. Many of the features of the software are beyond the scope of an introductory course, and therefore this book does not discuss them. However, if you are curious or adventurous, you should explore the menus and Help system as well as the JMP website. You might find a quicker, more intuitive, or more interesting way to approach a problem. For most of the topics addressed in the book, you will see an introduction. There is almost always more to know.

      What Should You Know about the Examples?

      Real statistical investigations begin with pressing, important, or interesting questions, rather than with a set of techniques. Researchers do not begin a study by saying “Today is a good day to compute some standard deviations.” Instead, they pose questions that can be pursued by analyzing data and follow a relatively straightforward protocol to refine the question, generate or gather suitable data, apply appropriate methods, and interpret their findings. The chapters in this book present questions that I hope you will find interesting, and then rely on the data tables provided to search for answers. The questions and analyses become progressively more challenging through the book.

      Software Used to Develop the Book’s Content

      The book was developed using pre-production versions of JMP15 Pro. The essential examples work with JMP. Whenever a section illustrates JMP Pro functionality, that fact is clearly announced.

      Example Data

      As previously noted, each of the data tables referenced within the book contains real data, much of it downloaded from public websites. There are 45 different data tables, most of which have been updated for this edition. Readers should download all of the JMP data tables via the author page at support.sas.com/carver. Appendix A describes each file and its source. Many of the tables include columns (variables) in addition to those featured in exercises and examples. These variables might be useful for projects or other assignments.

      Where Are the Exercise Solutions?

      Solutions to the scenario questions are available via the author page at support.sas.com/carver. Instructors who adopt the book will be able to access all solutions. Students and other readers can find solutions to the even-numbered problems at the same site.

      Thanks and Acknowledgments

      This first edition of this book began at the urging of Curt Hinrichs, the Academic Program Manager for JMP. This led to conversations with Julie Palmieri, Editor-in-Chief at SAS Press at the time, after which the project started to take shape. I have had the great good fortune to work with a different editor for each edition: Stephenie Joyner, Sian Roberts, and, most recently, Catherine Connolly have kept this little trolley on the

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