Contributed by Brenda and José Ramírez, authors of Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide
A few years ago an exciting and wonderful opportunity presented itself to us. The JMP team approached us with the idea to write a book for engineers and scientists. From a professional standpoint, we were confident that we could do it because we have 20 years of experience collaborating with engineers and scientists in using statistics and JMP as a catalyst for new discoveries and insights. However, we also knew that this was not going to be an easy task because we would have to balance this project with our family life, raising our daughter, and our full time jobs as industrial statisticians.
In addition to juggling our schedules, we also knew that extra care would be needed when dealing with issues of how we approach the creative process, and the difficulty of blending different writing styles, in order to maintain our peaceful existence as husband and wife. Some of the people we know were, and still are, amazed that we were not only writing a book together but that it was a statistics book. Are you kidding? “We cannot even write a grocery list together,” some commented. In fact we often joke that our next book will be titled “We wrote a book together and we survived.”
Our journey officially began in the fall of 2006 when we signed the final version of our publishing agreement with SAS Press. We quickly realized that this was going to be a lot of work. The first sample chapter was about 50 pages long and took us about 100 hours to complete, before we submitted it for the first round of technical and editorial reviews. Trying to steal time to write for a few hours in the evenings and on the weekends did not work well, and we found ourselves carving out larger junks of time to be able to get into a rhythm and maintain it. Oh, and did we mention that it is really, really, important to back up your work on a regular basis? At one point, we had a hard drive disk crash and actually lost Chapter 3, yes, all 50 pages of hard work, including JMP tables, figures, text, and 40 vacation hours gone! (Note from José: It will be on my tombstone: “He Did Not Back Up Chapter 3”).
When we submitted all seven chapters for type setting, and before the final editing of our book, we felt very happy and thought that the hardest part of this process was behind us. This occurred approximately 30 months after we first took pen to paper, oops, fingertips to keyboard. As we discussed the last leg of the time line with our awesome editor, Stephenie Joyner, it seemed like we had plenty of time available for submitting final edits in order to have the book available for the 2009 JMP Discovery conference in Chicago. Boy, were we in for a surprise!
The final editing process took us back to our days in grad school. I’m sure some of you will remember those endless nights cramming for finals or trying to complete your dissertation and the only thing that kept you going was a mega dose of caffeine. Only back then, we were wired this way. Now fast-forward a couple of decades and you will understand that this is not a memory worth repeating. In order to allow time for the creation of the index and several weeks for printing before the conference, we needed to turn around the final edits for each chapter within 48 hours. It will be a long time before we forget how a much needed romantic get away to Vermont turned into power editing sessions that began at 6:00 am and ended at 2:00 am.
The inspiration for our book comes from the National Bureau of Standards Handbook 91 Experimental Statistics by Mary Natrella. In writing this book we wanted to bring the spirit and usefulness of the NBS Handbook 91 to the countless engineers, scientists, and data analysts whose work requires them to transform data into useful and actionable information. We also envisioned that our book would be strategically placed in the offices of our readers for easy and frequent access for solving common problems in industry using JMP.
In order to accomplish this, we use case studies throughout the book along with a 7-step problem-solving framework, with a strong emphasis on the problem set up, interpretation, and translation of the results in the context of the problem. We also provide a practical overview of the underpinnings and provide appropriate references for those who want to learn more about the statistical techniques and concepts. Finally, for those who want to learn how to benefit from the power of JMP, we have loaded the book with many step-by-step instructions and tips and tricks.
The case studies used in our book are based upon common problems that engineers or scientist will come across at some point in their careers, with the chapter headings reflecting the specific application. As an example, in Chapter 4, “Comparing the Measured Performance of a Material, Process, or Product to a Standard,” we use a semiconductor example involving a new three-zone vertical furnace for thin film deposition of wafers to illustrate the useful of one sample significance tests to qualify a new piece of equipment. In Chapter 7, “Characterizing Linear Relationships between Two Variables,” we use simple linear regression to develop a calibration curve for a canister-style load cell design that is used in cargo truck weighing systems. In Chapter 7 we also showcase the data from Albert Einstein’s first published paper, back in 1901, to investigate the nature of intermolecular forces.
Our journey has reached a key milestone with the publishing of Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide in September 2009. Even though it was long and challenging, we are thrilled and proud to be able to leave such a legacy for our daughter and future generations of scientists and engineers to enjoy. But this is not the end of our journey by any stretch of the imagination. In October we launched our blog, Stat Insights, as another vehicle for sharing our experiences with those who care to listen and, we are starting to think about our second book, Analyzing and Interpreting Categorical Data Using JMP: A Step-by-Step Guide. Crazy or enthusiastic, you be the judge!
