There are two common definitions of statistics. The first is "turning data into information", the second is "making inferences about populations from samples". These two definitions are quite different, but between them they capture most of what you will learn in most introductory statistics courses. The first, "turning data into information," is a good definition of descriptive statistics—the topic of the first part of this, and most, introductory texts. The second, "making inferences about populations from samples", is a good definition of inferential statistics —the topic of the latter part of this, and most, introductory texts.
To reach an understanding of the second definition an understanding of the first definition is needed; that is why we will study descriptive statistics before inferential statistics. To reach an understanding of how to turn data into information, an understanding of some terms and concepts is needed. This first chapter provides an explanation of the terms and concepts you will need before you can do anything statistical.
Before starting in on statistics, I want to introduce you to the two young managers who will be using statistics to solve problems throughout this book. Ann Howard and Kevin Schmidt just graduated from college last year, and were hired as "Assistants to the General Manager" at Foothill Mills, a small manufacturer of socks, stockings, and pantyhose. Since Foothill is a small firm, Ann and Kevin get a wide variety of assignments. Their boss, John McGrath, knows a lot about knitting hosiery, but is from the old school of management, and doesn't know much about using statistics to solve business problems. We will see Ann or Kevin, or both, in every chapter. By the end of the book, they may solve enough problems, and use enough statistics, to earn promotions.
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