Business Statistics Made Easy in SAS

Book Preface

Introduction to the Book

Welcome to Business Statistics Made Easy in SAS by Professor Gregory John Lee.

This book is a breakthrough in business statistics learning, with a fresh new approach to explaining and teaching the exciting area of data analysis.

This book is designed as a user-friendly, practice-oriented text to teach businesspeople, students and others core statistics concepts and applications.Business Statistics Made Easy in SAS steers away from complex mathematical-based explanations, and also avoids basing the explanations on traditional concepts such as distributions, probability theory and the like, which tend to lose the practice-oriented reader.

Instead of these traditional approaches, this book employs many features that haveproved successful in a great number of MBA and other classes, some of which are completely innovative. These features include the following:

1 Unique templates for understanding statistics: There are several chapters that present a process template overview of statistical thinking, in other words, they attempt to show the reader how the general process of statistical thinking works. These chapters are a completely fresh way to teach people how statistics works as a whole. Chapter 2 gives a process overview of statistics in general; Chapter 11, an overview of statistical analysis as a process; and Chapter 12, an overview of how to analyze a given statistic after it is generated. These chapters are mostly innovative, and enable readers to grasp the statistical method as a whole rather than learning this in the traditional way, in which a person is expected to learn individual techniques and concepts, and then piece them together to form the bigger concept of the statistical method.

2 Extrapolation of statistics to business strategy, financial impact, and problem solving: I believe that one of the weaknesses of traditional statistics texts, from the point of view of the average business reader, is the lack of application beyond the statistics itself. I attempt to overcome this through two completely innovative chapters that take statistical outcomes and extrapolate findings to much broader implications, such as the profitability of business cases. This allows readers to answer the question “Why should I care?” that so often plagues statistics courses. I also take this approach extensively in practice questions.

3 Binding case: At the beginning, in Chapter 1, I build a central, illustrative statistical case that most of the rest of the text builds on and uses throughout for illustration. This helps to focus the discussion and ground readers in a well-understood context.

4 Practicality through SAS® Studio or SAS®9: The core idea behind the text is to focus on practical implementation through a specific statistics package, in this case SAS. The book has been written to work well for both the exciting new SAS Studio as well as SAS 9 (specifically I use SAS 9.4 or SAS 9.3). Extensive screenshots of each major step are provided to guide the user carefully through using the package, and the data and prewritten code used for every example are given with the textbook, which the reader can simply open and run to get the output. The reader can then usually change dataset and variable names to run the same programs on other data situations.

5 Non-technical exposition: There is very little mathematical development, aside from some limited development in appendices for the interested reader. The text is developed verbally in a logical and clear way, often using metaphorical analogies that help the reader to connect the statistics concepts to life examples with which he or she is familiar. I avoid starting off with hard-to-understand terminology; instead I ease the reader into it from the perspective of what the terminology is really trying to achieve.

6 Pictorial and metaphorical explanations: There is extensive use of unique pictorial and metaphorical explanations – not just diagrams but various different figures that help to explain the concepts. This proves exceptionally useful for teaching the less technical user, and adds completely new pedagogical features to many difficult sections, such as the one on the concept of power. I also include decision-making flowcharts for some techniques that have been hugely popular with readers.

7 Case vignettes: I also have other illustrative cases of actual statistics applications in real life to help readers see the applicability of the techniques.

8 Practice questions and datasets: I include a large number of practice questions and datasets. I also run online assessments that readers can take to self-assess or instructors might use to assess; these may be adjusted for the text.