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Description: Hoboken, NJ : John Wiley & Sons, Inc., 2018. | Includes bibliographical references and index. |

Identifiers: LCCN 2017051197 (print) | LCCN 2017054561 (ebook) | ISBN 9781119138365 (pdf) | ISBN 9781119138372 (epub) | ISBN 9781119138358 (pbk.)

Classification: LCC HF1017 (ebook) | LCC HF1017 .M37 2018 (print) | DDC 519.5-dc23

Cover Image: Derivative of “Rock Climbing in Joshua Tree National Park“ by Contributor7001 is licensed under CC BY-SA

Dedicated to my students who managed to stay awake during class, and to my family who are clearly a few standard deviations above the mean: Marta, Leo, Sofia, and Oscar

Preface

When the Boston Red Sox traded Babe Ruth to the New York Yankees in 1919, they were one of the most successful baseball teams in history. At that time, the Red Sox held five World Series titles, with the most recent in 1918. That trade would start an 86-year dry spell for the Red Sox, during which they would not win a single national title. That trade would start what baseball fans know as the Curse of the Bambino. The Curse supposedly made Johnny Pesky hesitate at shortstop in a routine throw home in game seven of the 1946 World Series. The Curse showed up when Bob Stanley threw a wild pitch in game six of the 1986 World Series that let the tying run in, and stayed to see Bill Buckner let a ground ball pass between his legs at first base. The Red Sox finally broke the curse in 2004 beating the St. Louis Cardinals. How did the Boston Red Sox break the Curse of the Bambino? Statistics.

Ok, perhaps attributing the Red Sox's 2004 title and the two that followed entirely to statistics is a bit of a reach. Statistics, however, played a role. In 2002, Theo Epstein was hired as the general manager (GM) for the Red Sox. He was the youngest GM in the history of major league baseball. Epstein relied heavily on statistics when building team rosters and making managerial decisions. He was an early adopter of what is called sabermetrics – which is a statistical analysis of baseball. His approach focused on utilizing undervalued players, including those who were on the verge of leaving the game because no other team would sign them. The movement was away from flashy players with big risks and big rewards to the more inconspicuous workhorses. It worked. Of course, it is possible that Theo Epstein and the Boston Red Sox just got lucky. Consider, however, that Theo Epstein was hired as the President of Baseball Operations for the Chicago Cubs in 2011. In 2016, the Cubs would win their first World Series in 108 years. It would end yet another curse – the Curse of the Billy Goat – that prevented the Cubs from winning for 71 years. Again, statistics.

Addressing Two Challenges

Over the past dozen years, I have taught courses in business statistics to thousands of undergraduate students. As an instructor, one of the challenges with teaching statistics is trying to convince students that the material is important. I usually take two approaches. The first is to persuade students that they need to understand statistics as consumers of information. We are bombarded with information every single day and it is coming at us from every direction. Our news sources and social media platforms are crawling with statistics. On a Monday, I may learn that coffee is good for me and by Wednesday it is now the kiss of death. In the 1980s, eggs were cholesterol-filled heart attack triggers and today they are considered the perfect food. On any given day, I can read about studies that tell me how to live longer, run faster, have more energy, make more money, be a better parent, and be happier. These types of studies all rely on statistics. Some of the information we get is from scientific studies – those that rely on the scientific method – but other information is very ad hoc. Understanding what the statistics tell us, how they are calculated, and the samples they are derived from is key to processing all of the information we consume. Understanding statistics can help you pick out the nuggets of useful information from the big mess of the modern information age.

The other approach I take in trying to convey the importance of statistics is to appeal to the students as producers of information. It is probably safe to assume that most people do not enjoy cranking through formulas and pouring over spreadsheets of data. However, everyone is interested in something. Perhaps, you are interested in investing in the stock market and you need to decide which firms to invest in. Maybe you need to convince your boss which social media platform to advertise on. Maybe you need to persuade your parents that spending a semester studying abroad is a useful experience. The point is that everyone has interesting questions, and answering those questions usually requires some form of data analysis. Just having data is not enough, you need to know how to release its secrets.

The second challenge with teaching statistics is that, in my experience, many students dread the thought of the subject, and often walk through the door the first day of class already resigned to the idea that they will hate it. Typically, students believe that they will dislike statistics because they consider the subject too hard, or it requires too much math. Adding to the list of students' fears and concerns is the fact that most of the materials created for undergraduate courses in business statistics try to accomplish too many things and as a result are overwhelming. Textbooks try to balance a mix of theory, intuition, formulas, case studies, datasets, applets, problem sets, and the practical use of particular software programs. All of these are important objectives, but when blended together each tends to get crowded out. In my experience, students use their statistics textbooks as reference guides to look up formulas or functions, but in the process miss the fundamental concepts and intuition.

The objective of this book is to try help ease both of these challenges. The goal of each chapter is to first motivate a particular section of business statistics and then walk through the concepts in an intuitive fashion. The book is driven by examples and many of the examples span over multiple chapters. The book was written with a goal of removing many of the distractions students encounter in their statistics textbooks. Mathematical formulas and much of the notation are relegated to technical appendices at the end of each chapter. There are no online applets, data downloads, or breakout case studies. The prose is written so that it is hopefully inviting to students with different backgrounds and experiences. The focus is more on developing intuition and understanding the fundamentals than it is on being a comprehensive catalog of statistical tests.

How to Use This Book

This book is not designed to be used as a primary source of information for an undergraduate statistics course. It does not cover every figure, statistic, or hypothesis test you will find in a comprehensive textbook. It is meant to be a supplement to a more detailed textbook and/or a set of lecture notes. It should be thought of as a companion guide with the goal of helping students get a better grasp on the fundamentals. In this way, the primary textbook serves as the comprehensive catalog of information and, perhaps, the source of assessment materials, while A Guide to Business Statistics serves as the source for students to strengthen their intuition about the concepts and their applicability. However, for classes in which the instructor provides all the required technical details in the lecture notes and does not rely on a textbook to assign problems, homework, or practice datasets, A Guide to Business Statistics can serve as a primary textbook. In these cases, students will read the book to complement the material covered in lecture with the goal of providing an intuitive and example-driven approach to better understand the material. This book maintains the level of rigor of a standard textbook in business statistics, but with a more streamlined approach and accessible explanation of the material.

It is not surprising that most students do not read their undergraduate statistics textbooks in a linear fashion. If anything, they tend to skim through the pages in search for formulas, tables, or functions. The chapters in most statistics textbooks are very difficult to read from start to finish, and to be fair they are not designed for that approach. This book is designed to be easy to read and, most importantly, concise. Students should open a chapter and read it from start to finish and at the end have a good understanding of the core concepts for that section. The chapters include examples, simple tables and figures, and a technical appendix with the formulas. At the end of each chapter (before the appendix), the key elements are reinforced in a brief summary paragraph. To maintain its readability in a linear fashion, it purposefully avoids problem sets, animations, video clips, and interactive materials.

Another important distinction between standard textbooks and A Guide to Business Statistics is the treatment of statistical software programs. Textbooks are increasingly focused on how to better integrate statistics software (e.g., Excel, SPSS, and Minitab) with the course material. This is important because students should be able to use technology to analyze data and produce statistical output. However, while many students are capable of running a statistical test in a program like Excel, there is often a lack of general understanding regarding the underlying concepts and interpretations of the results. For example, most students can successfully create a confidence interval if provided a dataset. Fewer students can correctly interpret a confidence interval, and even fewer can still explain the theorems those interpretations are grounded in. I would argue that understanding the underlying concepts in statistics is more important than learning how to use a certain software package to generate statistical output. The technology is going to change, but the concepts and theorems that are fundamental to statistics are not tied to specific platforms. This book does contain references to statistical functions in Excel, especially in the chapters on regression analysis. Software programs like Excel are absolutely required for any analysis of large datasets. The point of this book, however, is not to develop a student's skill set in any particular software program. Running a regression in Excel is just as easy as in SPSS or Minitab. The point, rather, is to help interpret the output that is produced by any software program.

The trajectory of the chapters follows most of the standard textbooks in business statistics. The coverage of the material in each chapter is designed to be more “narrow and deep” rather than “broad and shallow.” That said, in my experience, all of the key materials required in a first and second course in undergraduate business statistics are covered in this book. The first part of the book is concentrated on how we collect and describe data (Chapters 1–6) and the second half is focused on how to use sample data to make inferences about things we do not know about a population of interest (Chapters 7–13). The chapters on inferential statistics focus on parametric tests – those that assume that the data follow a particular type of distribution. These are the most common tests in business and other social sciences. The final three chapters of the book cover linear regression techniques.

Target Audience

This book should serve as a useful guide for all undergraduate statistics students in business and economics, regardless of the specific primary textbook (if any) they are using in their course. Almost all business and economics majors are required to complete a course in statistics, and many 4-year business programs require two courses as part of the major. In addition, most 2-year colleges offer an introductory course in statistics. When two courses are required, it is often the case that the same primary textbook is used in both courses. A Guide to Business Statistics is geared to students taking both their first and second courses in statistics. The first course is typically taken as a freshman or sophomore and the second as a junior or senior. The book, therefore, should prove useful over all four undergraduate years.

Although the book is geared toward students in higher education, it may be a helpful resource to faculty and instructors who have been away from statistics for some time. It can serve as a concise “refresher” resource for teachers and practitioners.