Practical Data Analysis with JMP, Third Edition. Robert Carver
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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 tracks.
At SAS Press, so many people have contributed to the planning and execution of the book in its development. For this edition, Sian Roberts is now Publisher. Suzanne Morgen handled the copyediting, Denise Jones the production, Robert Harris the cover design, and Missy Hannah the marketing effort.
Earlier editions were shaped and tended by Shelley Sessoms, Stacey Hamilton, Shelly Goodin, Mary Beth Steinbach, Cindy Puryear, Brenna Leath, Brad Kellam, Candy Farrell, Patrice Cherry, and Jennifer Dilley. My enduring thanks go to them all.
Many other professionals at JMP have influenced and informed the content of this book at critical points along the way. I am very grateful to John Sall, Xan Gregg, Jon Weisz, Brad Jones, Brady Brady, Jonathan Gatlin, Jeff Perkinson, Ian Cox, Chuck Pirrello, Brian Corcoran, Christopher Gotwalt, Curt Hinrichs, Mia Stephens, Volker Kraft, Julian Parris, Ruth Hummel, Kathleen Watts, Mary Loveless, Gail Massari, Lori Harris, Holly McGill, Peng Liu, and Eric Hill for encouraging me, answering my questions, setting me straight, and listening to my thoughts. To this group I send a special shout-out to JMP Senior Systems Engineer Rob Lievense, who has been a consistent advocate and supporter of this work.
I am especially thankful for the care and attention of those people who have reviewed this and the prior editions. Technical reviews of the current edition were provided by Mark Bailey, Duane Hayes, and Kristen Bradford. Mark has been the constant among reviewers, having made invaluable recommendations to all three editions. Performing double duty on the first two editions were Tonya Mauldin and Sue Walsh. Fang Chen, Paul Marovich, and Volker Kraft rounded out the many superb reviewers. Collectively, their critiques tightened and improved this book, and whatever deficiencies that may remain are entirely mine.
Naturally, the completion of a book requires time, space, and an amenable environment. I want to express public thanks to three institutions that provided facilities, time, and atmospherics suitable for steady work on this project. My home institution, Stonehill College, was exceptionally supportive, particularly through the efforts of Provost Joe Favazza and my chairperson, Debra Salvucci, and Department Administrative Assistant Carolyn McGuinness. Colleagues Dick Gariepy and Michael Salé generously tested several chapters and problems in their classrooms, and Jan Harrison and Susan Wall of our IT Department eased several technical aspects of this project as well.
Colleagues and students at the International Business School at Brandeis University sharpened my pedagogy and inspired numerous examples found in the book. During a sabbatical leave from Stonehill, Babson College was good enough to offer a visiting position and a wonderful place to write the first edition. For that opportunity, thanks go to Provost Shahid Ansari, former chairperson Norean Radke Sharpe, then-chair Steve Ericksen, and colleagues John McKenzie and George Recck.
During the summer of 2013, the Stonehill Undergraduate Research Experience (SURE) program provided a grant to support this work with time, space, and finances. Carolyn Moodie (Class of 2015) was a superior and self-directed research collaborator, assisting in the critical phases of problem formulation, data identification, data cleaning and exploratory analysis. Carolyn also brought a keen eye to editorial tasks, and willingly gave her feedback on which topics student readers might find engaging. Thanks also to Bonnie Troupe for her skillful administration of the SURE program. During the spring and summer of 2013, Stonehill students Dan Doherty, Erin Hollander, and Tate Molaghan also pitched in with editorial and research assistance.
Special acknowledgment also goes to former Stonehill students from BUS207 (Intermediate Statistics) who “road tested” several chapters, and very considerable thanks to three students who assisted greatly in shaping prose and examples, as well as developing solutions to scenario problems: Frank Groccia, Dan Bouchard, and Matt Arey. Later students in BUS206 (Quantitative Analysis for Business) at Stonehill also class-tested several chapters and exercises.
Several of the data tables came through the gracious permission of their original authors and compilers. I gratefully acknowledge the permission granted by my good friend George Aronson for the Maine SW table; by Prof. Max A. Little for the Parkinson’s disease vocal data; by Prof. Jesper Rydén for the Sonatas data table (from which the Haydn and Mozart tables were extracted); by Prof. John Holcomb for the North Carolina birth weight data; and by Prof. I-Cheng Yeh for the Concrete table and the two subsets from that data.
In recent years, my thoughts about what is important in statistics education have been radically reshaped by colleagues in the ISOSTAT listserv and the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE) and the U.S. Conference on Teaching Statistics that CAUSE organizes every two years. The May 2013 CAUSE-sponsored workshop “Teaching the Statistical Investigation Process with Randomization-Based Inference” given by Beth Chance, Allan Rossman, and Nathan Tintle influenced some of the changes in my presentation of inference. Over an even longer period, our local group of New England Isolated Statisticians and the great work of the ASA’s Section on Statistics Education influence me daily in the classroom and at the keyboard.
Finally, it is a pleasure to thank my family. My sons, Sam and Ben, keep me modest and regularly provide inspiration and insight. My wife Donna—partner, friend, wordsmith extraordinaire—has my love and thanks for unflagging