An Introduction to Modern Business Statistics
- ISBN-10
- 0534358195
- ISBN-13
- 9780534358198
- Category
- Mathematics / Probability & Statistics / General
- Pages
- 683
- Language
- English
- Published
- 1999
- Publisher
- Duxbury Press
- Authors
- George C. Canavos, Don M. Miller
Description
Using the computer to eliminate rote computation and facilitate learning, this book inspires and motivates readers to learn statistics by showing them its great practical importance to their careers. In every chapter, the authors include an ample number of examples and vignettes that illustrate and emphasize skills that enable students to interpret data effectively and to convert data into usable information. This approach enhances students' abilities to make better decisions, thus preparing them to exert greater influence in their future careers. To reinforce the idea that statistics is the linkage that transforms data into useful information, thereby enhancing planning and decision making, almost every numbered example includes introductory language that articulates the importance of the illustration in a functional area of business. The authors use Microsoft Excel, MINITAB, and JMP IN statistical software to execute statistical methods--presenting computer outputs and interpretation first; then illustrating the method using statistical tables. In addition, to promote the learning of fundamentals, the authors also take the users through many methods step-by-step, using examples with very small data sets. Chapter appendices provide clear, detailed instructions on the use of Excel, MINITAB, and JMP IN. Users are not just purchasing a textbook--every new copy of the book is packaged with a student software and data disk. This disk contains Data Analysis Plus Add-ins for Microsoft Excel, as well as all the data sets used in the book formatted for Excel, MINITAB, JMP IN, and ASCII. In addition to the many examples and exercises they included in the First Edition, the authors add approximately 120 exercises based on published articles in academic journals, the popular media, or widely available sources of data. Many of these exercises contain large data sets, and many are revisited is subsequent chapters.
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