Preface
The study and use of statistics have come a long way since the advent of computers. Particularly, computers have reduced both the effort and the time involved in the statistical analysis of data. But this ease of use has been accompanied by some difficulties. As computers became more and more proficient at carrying out statistical operations of increasing complexity, the actual operations—and what they actually meant and did—became more and more distant from the user. It became possible to do a wide variety of statistical operations with a few lines or words of commands to the computer. But the average student, even the average serious user of statistics, found the increasingly complex operations increasingly difficult to access and understand.
Introducing Excel
Sometime in the late 1980s, Microsoft Excel became available, and with it came the ability to carry out a wide range of statistical operations—and to understand the operations that were being carried out—in a spreadsheet format. John's first introduction to Excel was a revelation. It came during his MBA studies and continued through his doctoral studies and even in his first industry job. In fact, John quickly became somewhat indispensable in that first industry job for the plain fact that he was the most proficient of his peers at Excel. Through the years he found himself using Excel to complete all kinds of tasks (since he was too stubborn to learn to program properly). He discovered that Excel was not only a powerful statistical tool but also, more important, a powerful learning tool. When he began to teach the introductory course in business decision modeling to MBA students, Excel seemed to him to be the obvious medium for the course.
So How Did We Get to Here?
At the time John started using Excel in his teaching, there were a few textbooks devoted to statistics using Excel. However, none fit his needs very well, so he wrote Spreadsheet Modeling for Business Decision Modeling. That was about the time John met David. David had earned his doctorate in technology management and had worked in the health care industry for more than 10 years (which ensures that the health care–specific examples and scenarios used in this book are appropriate). He discovered the power of Excel's statistical analysis functionality by using it to calculate the multiple regression and correlation analysis required for his doctoral dissertation.
Through his friend, Scott Bankard, John learned that the author of a successful text in the use of Excel to solve statistical problems in health care administration was looking for someone to revise that text. In turn, John and David became the coauthors of the revised text.
Intended Level of the Textbook
The original text was designed as an introductory statistics text for students at the advanced undergraduate level or for a first course in statistics at the master's degree level. It was intended to stand alone as the book for the only course a student might have in statistics. The same is true for the revised text, which includes some enhancements and updates that provide a good foundation for more advanced courses as well. Furthermore, since the book relies on Excel for all the calculations of the statistical applications, it was also designed to provide a statistical reference for people working in the health field who may have access to Excel but not to other dedicated statistical software. This is valuable in that a copy of Excel resides on the PC of almost every health care professional. Further, no additional appropriations would have to be made for proprietary software and there would be no wait for the “stat folks.”
Textbook Organization
The revised edition of the text has been updated for use with Microsoft Office Excel 2013. It provides succinct instruction in the most commonly used techniques and shows how these tools can be implemented using the most current version of Excel for Windows. The revised text also focuses on developing both algebraic and spreadsheet modeling skills. Algebraic formulation and spreadsheets are juxtaposed to help develop conceptual thinking skills. Step-by-step instructions in Excel 2013 and numerous annotated screenshots make examples easy to follow and understand. Emphasis is placed on the model formulation and interpretation rather than on computer code or algorithms.
The book is organized into two major parts: Part 1, Chapters 1 through 6, presents Excel as a statistical tool and discusses hypothesis testing. Part 1 introduces the use of statistics in health policy and health administration–related fields, Excel as a statistical tool, data preparation and the data display capabilities of Excel, and probability, the foundation of statistical analysis. For students and other users of the book truly familiar with Excel, much of the material in Chapter 2, Chapter 3, and Chapter 4, particularly, could be covered very quickly.
Part 2, which includes Chapters 7 through 14, is devoted to the subject of hypothesis testing, the basic function of statistical analysis. Chapter 7 provides a general introduction to the concept of hypothesis testing. Each subsequent chapter provides a description of the major hypothesis testing tool for a specific type of data. Chapter 8 discusses the use of the chi-square statistic for assessing data for which both the independent and dependent variables are categorical. Chapter 9, on t tests, discusses the use of the t test for assessing data in which the independent variable is a two-level categorical variable and the dependent variable is a numerical variable. Chapter 10 is devoted to analysis of variance, which provides an analytical tool for a multilevel categorical independent variable and a numerical dependent variable. Chapters 11 through 13 are devoted to several aspects of regression analysis, which deals with numerical variables both as independent and dependent variables. Finally, Chapter 14 deals with numerical independent variables and dependent variables that are categorical and take on only two levels and introduces the use of Logit.
Leading by Example(s)
Each chapter of the book is structured around examples demonstrated extensively with the use of Excel displays. The chapters are divided into sections, most of which include step-by-step discussions of how statistical problems are solved using Excel, including the Excel formulae. Each section in a chapter is followed by exercises that address the material covered in that section. Most of these exercises include the replication of examples from that section. The purpose is to provide students an immediate reference with which to compare their work and determine whether they are able to correctly carry out the procedure involved. Additional exercises are provided on the same subjects for further practice and to reinforce the learning gained from the section. Data for all the exercises are included on the web at www.wiley.com/go/kros3e , and may be accessed by file references given in the examples themselves. Additional materials, such as videos, podcasts, and readings, can be found at www.josseybasspublichealth.com.
A supplemental package available to instructors includes all answers to the section exercises. In addition, the supplemental package will contain exam questions with answers and selected Excel spreadsheets that can be used for class presentations, along with suggestions for presenting these materials in a classroom. However, the book can be effectively used for teaching without the additional supplemental material.
Users who would like to provide feedback, suggestions, corrections, examples of applications, or whatever else can e-mail me at [email protected].
Please feel free to contact me and provide any comments you feel are appropriate.