Curt Hinrichs

JMP Essentials


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JMP software and learning resources. Curt and his team are charged with developing JMP users among the next generation of data analytics professionals. They work directly with faculty, authors, and administrators and partner with leading academic societies, publishers, and service providers to support the effective use of JMP software in the classroom. Prior to joining SAS, Curt worked as an editor and publisher for Thomson Learning, and its Mathematics and Statistics Publishing Group. He holds a degree in economics from San Diego State University.

Figure 1.1 Some JMP Help Options

      CHUCK BOILER is a US Systems Engineer Manager for JMP, a business unit of SAS. Since joining SAS, Chuck has held management roles with JMP and helped develop solutions for conducting many types of analysis, including design of experiments for the semiconductor industry, quality control for pharmaceutical manufacturing, and marketing applications for survey analysis using JMP software. He now works with field engineering staff and customers to help them solve problems and discover hidden opportunities in the data. Prior to joining SAS, Chuck worked as technical services manager and software quality assurance manager for Abacus Concepts. A member of the American Society of Quality, Chuck received a bachelor’s degree in education from the University of Oregon and has done graduate work in ancient philosophy at the Graduate Theological Union in Berkeley, California. He is a graduate of Gallup University’s Great Manager Program.

Figure 1.1 Some JMP Help Options

      SUE WALSH worked for 10 years as a SAS Technical Support Statistician supporting JMP. Prior to working in Technical Support, she worked at SAS as a Statistical Training Specialist, teaching both SAS and JMP to users, and as an Analytic Consultant, supporting the use of SAS in colleges and universities across the country. Sue has over 10 years experience teaching mathematics and statistics at community colleges. She was the first woman commissioned from the Air Force ROTC program at Manhattan College. She retired with a total of 23 years of service in the US Air Force and Reserve. Sue holds a master of business administration from Rensselaer Polytechnic Institute in Troy, New York and a master of science in applied statistics from Wright State University in Dayton, OH.

      Learn more about these authors by visiting their author pages, where you can download free book excerpts, access example code and data, read the latest reviews, get updates, and more:

      http://support.sas.com/hinrichs http://support.sas.com/boiler http://support.sas.com/walsh

      Acknowledgments

      We would first like to thank John Sall for creating a great product in JMP. Who knew that statistics could be so fun? If you are new to JMP, we hope it inspires you as it has us. Thanks also to Jon Weisz, Dave Richardson, Todd Hoffman, and Diana Levey for supporting the idea for this third edition.

      We have been very fortunate to work with the outstanding professionals at SAS Press. In particular, we would like to thank Catherine Connolly who has been our principal source of advice and support throughout the development process of this third edition. To Suzanne Morgen who helped us get to the essentials of what needed to be said. Thanks also to Denise Jones and Robert Harris for making it all work and look good, and to Sian Roberts for her encouragement and bringing this work to market.

      The manuscript for this book was substantially improved by the insightful suggestions of our reviewers. The book contains many new features and refinements due to their input. Our reviewers include:

      Chris Albright, Indiana University

      Mark Bailey, SAS Institute

      Kristen Bradford, SAS Institute

      Peter Bruce, Statistics.com

      Rob Carver, Brandeis University

      Laura Higgins, SAS Institute

      Ruth Hummel, SAS Institute

      Bob Lamphier, SAS Institute

      Sheila Loring, SAS Institute

      Paul Marovich, SAS Institute

      Gail Massari, SAS Institute

      Tonya Mauldin, SAS Institute

      Don McCormack, SAS Institute

      Di Michelson, SAS Institute

      Kemal Oflus, SAS Institute

      Chris Olsen, Grinnell College

      Jeff Perkinson, SAS Institute

      Lori Rothenberg, North Carolina State University

      Heath Rushing, SAS Institute

      Mia Stephens, SAS Institute

      Scott Wise, SAS Institute

      Annie Dudley Zangi, SAS Institute

      Richard Zink, SAS Institute

      We also wish to thank Sam Savage of Stanford University for testing the first edition in his class, and David Shultz and Mary Loveless for using the book with customer training.

      This book began with a desire to help the new JMP user and evolved into a labor of love. But without the love and incredible support of our families, friends, and colleagues this project would have never materialized. Thank you!

      Curt Hinrichs

      Chuck Boiler

      Sue Walsh

      San Francisco, CA and Raleigh, NC January 2020

      Chapter 1: Getting Started

       1.1 Using JMP Essentials

       1.2 Launching JMP

       1.3 JMP Menus

       1.4 Elements of Using JMP

       1.5 JMP Launch Dialog Windows

       1.6 The Excel Add-In (Optional)

       1.7 JMP Preferences

       1.8 Summary

      JMP was developed to help people with questions about their data get the answers that they need through the use of graphs and numerical results. For most people, memories of statistics can be a very unpleasant, if not forgotten, part of their education. If you see yourself as a new, occasional, or even reluctant user of data analysis, we want you to know that we have written this book for you.

      It is important to note that throughout the historical development of statistics as a scientific discipline, people had real problems that they needed to solve and developed statistical techniques to help solve them. Statistics can be thought of as sophisticated common sense, and JMP takes a practical, commonsense approach to solving data-driven problems.

      JMP was designed around the workflow of analyzing data rather than as a collection of tools only a statistician can understand. When you think about your data analysis problem, try to formulate the questions that might help you address it. For example, do you need to describe the variation in selling prices of homes in a city or understand the relationship of customer satisfaction with service waiting times? With this mindset, you will find the menus and navigation