About This Book

      What Does This Book Cover?

      Purpose: Learning to Reason Statistically

      We live in a world of uncertainty. Today more than ever before, we have vast resources of data available to shed light on crucial questions. But at the same time, the sheer volume and complexity of the “data deluge” can distract and overwhelm us. The goal of applied statistical analysis is to work with data to calibrate, cope with, and sometimes reduce uncertainty. Business decisions, public policies, scientific research, and news reporting are all shaped by statistical analysis and reasoning. Statistical thinking is an essential part of the boom in “big data analytics” in numerous professions. This book will help you use and discriminate among some fundamental techniques of analysis, and it will also help you engage in statistical thinking by analyzing real problems. You will come to see statistical investigations as an iterative process and will gain experience in the major phases of that process.

      To be an effective analyst or consumer of other people’s analyses, you must know how to use these techniques, when to use them, and how to communicate their implications. Knowing how to use these techniques involves mastery of computer software like JMP. Knowing when to use these techniques requires an understanding of the theory underlying the techniques and practice with applications of the theory. Knowing how to effectively communicate with consumers of an analysis or with other analysts requires a clear understanding of the theory and techniques, as well as clarity of expression, directed toward one’s audience.

      There was a time when a first course in statistics emphasized abstract theory, laborious computation, and small sets of artificial data—but not practical data analysis or interpretation. Those days are thankfully past, and now we can address all three of the skill sets just cited.

      Scope and Structure of This Book

      As a discipline, statistics is large and growing; the same is true of JMP. One paperback book must limit its scope, and the content boundaries of this book are set intentionally along several dimensions.

      First, this book provides considerable training in the basic functions of JMP 15. JMP is a full-featured, highly interactive, visual, and comprehensive package. The book assumes that you have the software at your school or office. The software’s capabilities extend far beyond an introductory course, and this book makes no attempt to “cover” the entire program. The book introduces students to its major platforms and essential features and should leave students with sufficient background and confidence to continue exploring on their own. Fortunately, the Help system and accompanying manuals are quite extensive, as are the learning resources available online at http://www.jmp.com.

      Second, the chapters largely follow a traditional sequence, making the book compatible with many current texts. As such, instructors and students will find it easy to use the book as a companion volume in an introductory course. Chapters are organized around core statistical concepts rather