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Business Statistics, 9th edition


Author: David F., Shannon, Patrick W., Fry, Phillip C

Publisher: Pearson


Publish Date: 2003

ISBN-10: 129202335X

Pages: 880

File Type: PDF

Language: English

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Book Preface

Why you need to know

A transformation is taking place in many organizations involving how managers are using data to help improve their decision making. Because of the recent advances in software and database systems, managers are able to analyze data in more depth than ever before. A new discipline called data mining is growing, and one of the fastest-growing career areas is referred to as business intelligence. Data mining or knowledge discovery is an interdisciplinary field involving primarily computer science and statistics. People working in this field are referred to as “data scientists.”

Doing an Internet search on data mining will yield a large number of sites talking about the field. In today’s workplace, you can have an immediate competitive edge over other new employees, and even those with more experience, by applying statistical analysis skills to real-world decision making. The purpose of this text is to assist in your learning process and to complement your instructor’s efforts in conveying how to apply a variety of important statistical procedures.

The major automakers such as GM, Ford, and Toyota maintain databases with information on production, quality, customer satisfaction, safety records, and much more. Walmart, the world’s largest retail chain, collects and manages massive amounts of data related to the operation of its stores throughout the world.

Its highly sophisticated database systems contain sales data, detailed customer data, employee satisfaction data, and much more. Governmental agencies amass extensive data on such things as unemployment, interest rates, incomes, and education. However, access to data is not limited to large companies. The relatively low cost of computer hard drives with 100-gigabyte or larger capacities makes it possible for small firms and even individuals to store vast amounts of data on desktop computers. But without some way to transform the data into useful information, the data these companies have gathered are of little value.

Transforming data into information is where business statistics comes in—the statistical procedures introduced in this text are those that are used to help transform data into information. This text focuses on the practical application of statistics; we do not develop the theory you would find in a mathematical statistics course. Will you need to use math in this course? Yes, but mainly the concepts covered in your college algebra course. Statistics does have its own terminology. You will need to learn various terms that have special statistical meaning.

You will also learn certain dos and don’ts related to statistics. But most importantly, you will learn specific methods to effectively convert data into information. Don’t try to memorize the concepts; rather, go to the next level oflearning called understanding. Once you understand the underlying concepts, you will be able to think statistically. Because data are the starting point for any statistical analysis, this text is devoted to discussing various aspects of data, from how to collect data to the different types of data that you will be analyzing. You need to gain an understanding of the where, why, and how of data and data collection.

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