visualized. (See Chapter 2).
2. They have a good idea of what graph they need and recognize it by its illustration or name and simply want to create it. (See Chapter 3.)
3. They really do not know what the data will say, and need help with exploring or with summarizing it. (See Chapter 4.)
4. They need to interpret or answer some specific questions about the data they have. (See Chapters 5 and 6.)
We also believe that the complete book is well suited as a reference guide to the following groups of users:
● Spreadsheet users who are looking for a convenient way to produce nice visualizations of their data or to supplement a spreadsheet’s statistical capabilities. JMP reads and writes data from a variety of programs including Microsoft Excel. This book provides a quick and easy way to make your spreadsheet data come alive and enables you to fully and interactively explore that data.
● Students enrolled in introductory statistics courses who may need JMP instruction. JMP is the ideal tool for students because its navigation reinforces the basic assumptions taught in an introductory course. This book provides an overview of the JMP tools needed in most first-year courses.
● SAS users who want to take advantage of JMP’s data visualization tools. We have provided Appendix A to illustrate the features of how JMP integrates with SAS.
Approach and Features
We have found that the best way to learn JMP is by using it and getting value out of it quickly. Our goal is to present the materials in this book in the most user-oriented approach possible. So, we have made every effort to organize the presentation around the new user’s common needs and questions and the most direct and concise means to answer them. We also recognize that the most basic use of data is in generating graphs of data rather than performing more complex statistical analyses. The following features are included for this purpose:
● We present the material with a show-and-tell approach. In most cases, we show you what the results look like alongside the conditions and steps required to produce them. We think this approach is especially useful for JMP users who have a good idea of what they want from JMP and just need the steps to create it.
● When appropriate, we provide an example-driven context for each JMP platform that explains its use, value, and general application to problems. We have tried to distill these contexts down to typical or easy-to-understand cases.
● We organize the contents into easily manageable chunks of information. While the entire book is designed to cover a fairly complete overview of the basics, each chapter represents one family of tasks (such as importing data, creating graphs, and sharing graphs).
● We hope you will keep this book near your computer. Within each chapter, we have designed each section to be self-contained enabling you to quickly find and execute the steps required to complete your task.
● No matter what your professional background, this book assumes only that you have a basic working knowledge of Microsoft Windows. Virtually all of the information in this book applies to using JMP on the Macintosh operating system, but only the Windows version of JMP is used in the examples.
Software Used to Develop This Content
This third edition of JMP Essentials was developed with JMP 15. Users of JMP Pro, JMP Student Edition or earlier releases of JMP will find nearly all of the instructions in this book suitable for their needs.
Organization
This book is designed like a cookbook. Find what you need and follow the steps. We have organized the contents of this book to reflect both the process of analyzing data (getting data, analyzing it, and sharing the results) and the progression from the very basic features in JMP to more specialized ones. We hope this organization offers the most value to the reader. Much of our judgment in this regard comes from our experience working one-on-one with new JMP users.
● Chapter 1 covers the preliminary material you will need for the rest of the book. The chapter identifies the conventions we use and introduces you to JMP menus, windows, and preferences.
● Chapter 2 covers the first step in any analysis: getting your data into JMP. With the exception of some material in Chapter 2, other chapters are self-contained, and you can read them in any order.
● Chapters 3 through 6 cover graphing and analysis:
◦ Chapter 3 is for the user who knows what graph he or she wants.
◦ Chapter 4 is for the user who does not know what the data says and needs to explore it to find an appropriate graph or summary. This chapter introduces maps.
◦ Chapters 5 and 6 are for the user who needs to solve a problem and answer questions using analytics and graphs.
● Chapter 7 covers topics related to sharing your graphs or results in a presentation, document, or through a browser.
● Chapter 8 covers additional resources that are available within JMP, online, and from outside resources, such as training, books, and user groups.
Figure 1 Chapter Organization
New to the Third Edition
It is gratifying to hear that previous editions have been useful to many new users of JMP. Our goal in writing this third edition is two-fold; first, to improve upon the core features and to that end, we have made many refinements, corrections and additions throughout the book based on feedback from users, colleagues, and reviewers. Secondly, in the five years since the second edition was published, JMP has added several important new features that we believe are Essential to the new user and we thought should be included. While there are many changes throughout the book, here is our Top Ten:
• Getting data out of database is a common task. Query Builder provides an easy, point and click interface to extract needed data. It also automatically creates SQL code that you can reuse on new data.
• An example of Join by matching columns is included. This is imperative when combining data tables where data in the tables to be joined is not in the same row order or does not have a one-to-one match.
• New graphs including Packed Bars, Parallel Plots, and Dot plots. JMP has been an innovator in visualization for many years. This continues with Packed Bar charts that are useful to summarize categorical variables with many (hundreds) of levels. Parallel plots are a useful way to express multivariate data. Finally, dot plots have been added. These plots commonly used in introductory statistics courses are simple but useful alternatives to histograms.
• Using Text Explorer to create a Word Cloud to visualize un-structured text that might arise as a result of customer comments, product reviews, or warranty claims for example.
• A new section, Comparing Two Continuous Columns, presents an introduction to simple linear regression analysis, which provides an equation for a line fit to the data. This equation provides a slope that defines the magnitude of the increase (or decrease) in a response column as the predictor column increases.
• Expansion of the discussion of the Fit Model platform and Prediction Profiler to include both continuous and categorical inputs.
• Revised information about the JMP Dashboard Builder. Combining multiple
