This book presents core topics in descriptive and inferential statistics with a rich assortment of business examples and real data, and an emphasis on decision-making. It contains a narrative writing style—and the captivating examples and applications, and rich data sets are woven right into the narrative. The examples are interesting, realistic and drawn from all areas of business and life. There is significant emphasis on using statistical software as a tool, with most examples presented in a spreadsheet environment using Excel and Minitab. Every topic is introduced in the context of a real business application complete with real data, from small and large data sets.
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PATRICK W. SHANNON, PH.D. is Professor of Production and Operations Management in the College of Business and Economics at Boise State University. He teaches graduate and undergraduate courses in business statistics, quality management, and production and operations management. In addition, Dr. Shannon has lectured and consulted in the statistical analysis and quality management areas for over 20 years. Listed among his consulting clients are Boise Cascade Corporation, Hewlett-Packard; PowerBar, Inc.; Potlatch Corporation; Woodgrain Millwork, Inc.; J.R. Simplot Company; Zilog Corporation; and numerous other public- and private-sector organizations. Professor Shannon has co-authored several university-level textbooks and has published numerous articles in such journals as Business Horizons, Interfaces, Journal of Simulation, Journal of Production and Inventory Control, Quality Progress, and Journal of Marketing Research. He obtained B.S. and M.S. degrees from the University of Montana and a Ph.D. in Statistics and Quantitative Methods from the University of Oregon.
DAVID F. GROEBNER is a Professor of Production Management and Chairman of the Department of Computer Information Systems and Production Management at Boise State University. He has bachelor's and master's degrees in Engineering and a Ph.D. in Business Administration. After working as an engineer, he has taught statistics and related subjects for 27 years. In addition to writing textbooks and academic papers, he has worked extensively with both small and large organizations, including Hewlett-Packard, Boise Cascade, Albertson's, and Ore-Ida. He has worked with numerous government agencies, including Boise City and the U.S. Air Force.
PHILLIP C. FRY is an Associate Professor in the Department of Computer Information Systems and Production Management in the College of Business and Economics at Boise State University, where he has taught since 1988. Phil received his B.A. and M.B.A degrees from the University of Arkansas, and his M.S. and Ph.D. degrees from Louisiana State University. His teaching and research interests are in the areas of business statistics, production management, and quantitative business modeling. In addition to his academic responsibilities, Phil has consulted with and provided training to small and large organizations, including Boise Cascade Corporation; Hewlett-Packard Corporation; The J.R. Simplot Company; United Water of Idaho; Woodgrain Millwork, Inc.; Boise City; and Micron Electronics.
Phil spends most of his free time with his wife Susan, to whom he has been married for 18 years, and his four children, Phillip Alexander, age 8, Alejandra Johanna, age 7, and twins, Courtney Rene and Candace Marie, age 1.
KENT D. SMITH received a Ph.D. in Applied Statistics from the University of California, Riverside in 1981. He holds a Master of Science degree in Statistics from the University of California, Riverside and a Master of Science degree in Systems Analysis from the Air Force Institute of Technology. His Bachelor of Arts degree in Mathematics was obtained from the University of Utah. Dr. Smith has served as a University Statistical Consultant at the University of California, Riverside and at California Polytechnic State University, San Luis Obispo. While at the University of California, he served as a consultant for the Biometrical Services Unit of the Biometrical Project at the University of California, Riverside. His private consulting has ranged from serving as an expert witness in legal cases, survey sampling for corporations and private researchers, medical and orthodontic research, and assisting graduate students with analysis required for master and doctoral degrees in various disciplines.
Dr. Smith began teaching as a part-time lecturer at the California State University, San Bernardino. While completing his doctoral dissertation, he served as a lecturer at the University of California, Riverside. Currently, he is a Professor of Statistics at the California Polytechnic State University, San Luis Obispo, one of the minority of universities that offer an undergraduate degree in statistics. The subjects he teaches include upper-division courses in regression, analysis of variance, nonparametrics, linear models, and probability and mathematical statistics, as well as a full array of service courses.Excerpt. © Reprinted by permission. All rights reserved.:
New business school graduates face an increasingly competitive job market. While the U.S. economy continues to perform well, corporate downsizing along with competitive pressures to trim costs have affected the demand for new graduates in most business majors. In order to stand out in today's competitive job market, graduates need to bring to an organization special skills and abilities that give them the potential to hit the ground running and contribute immediately.
One area where a student can have an immediate competitive advantage over both new graduates and existing employees is in the application of statistical analysis skills to business problems. While most colleges of business require their undergraduates and MBA-level students to have completed either one or two business statistics courses, too many students complete their academic programs without having mastered the statistical skills necessary to meet the needs of business. One reason for this may be that their statistics courses did not adequately prepare them in applying statistical tools and concepts to real-world decision-making problems.
Our intent in writing a third edition of A Course in Business Statistics is to build on the strengths of the previous two additions (readability, decision-making focus, content coverage, pedagogical aids, etc.) and to take the text to a new level of performance. In doing so, we have made substantive changes throughout the text so that students can more fully and completely appreciate the value of business statistics to both their academic and professional careers. Dr. Phil Fry of Boise State University and Dr. Kent Smith of Cal Polytechnic State University of San Luis Obispo have joined Professors David Groebner and Patrick Shannon as co-authors. All the authors share a passion for the subject, as well as a devotion to teaching, and have significant experience in applying the statistical tools in business and industry settings. Below is a description of the major improvements we have made to this edition.
STUDENTS USING REAL BUSINESS APPII(ATIONS
The third edition of A Course in Business Statistics provides real-world applications as a motivation for learning business statistics. While previous editions have focused on decision making and business applications, the new edition is more applied than ever before. Not only do the chapters focus on real companies and actual applications, increased effort has been placed on providing the student with an understanding of the role business statistics plays in decision making. This text is designed to help the instructor create a climate where students are motivated to learn and apply statistical techniques.
We believe that students will relate well to the writing style used throughout the text. The writing style and subject presentation are intended to facilitate student interest and involvement in the material. Statistical concepts and techniques are introduced through realistic business situations, and we have made every effort to communicate ideas using a nontechnical writing style. This is a business statistics text that students will actually read and use to increase their understanding of business statistics.
INCREASED COMPUTER EMPHASIS
To enhance the students' appreciation for business statistics, we emphasize computer-based analysis, rather than manual computations. Toward this end, Microsoft's Excel (Office 2000 version) is featured extensively throughout the textbook. Minitab is also used as a supplement to Excel at various places throughout the text. Chapter examples, exercises, and case studies are based on real industry data or data motivated by real-world examples. In this way, students gain a greater understanding of what statistical tools to use, when and how to apply them, and how to interpret the results of their analyses to decision making.
Unlike some computer-based textbooks that provided only end-of-chapter computer instructions, this text seamlessly integrates the computer applications with the text examples, always focusing on interpreting the output. The goal is for the students to appreciate the role of spreadsheet and statistical software as business statistics tools. We do not dwell on the specifics of how the software is used within the text. However, the screen shots do show the students the key instructions needed to generate the output they are seeing. In addition, callouts highlight the important output that is being discussed in the example. The following figure is typical of this approach.
TOOLS OF QUALITY
Statistics has played a major role in the quality movement. The third edition integrates quality concepts throughout the text. For example, many chapters contain one or more "Tools of Quality" segments. These segments, which are specially marked in the text, feature applications of statistical techniques (e.g., data check sheets, Pareto charts, and process capability analysis) that are frequently employed by organizations in their quality and process improvement activities. Many other examples and applications throughout the text have a quality theme. In addition, the CD-ROM that accompanies this text contains an entire chapter that presents an overview of quality issues and introduces statistical process control charts.
EXTENSIVE EXERCISE SETS
The Business Application Exercises at the end of each section provide realistic decision-making situations in which the statistical concepts from the section are applied. Not only do these exercises reinforce the statistical techniques presented in the book, but they also provide a useful motivation for the study of business statistics.
In addition to the end-of-section exercises, each chapter contains a complete listing of Conceptual Questions and Business Application Exercises at the end of the chapter. These end-of-chapter questions and problems require the student to identify what needs to be done and what statistical tool is required. In many instances, the problems are integrative by requiring students to draw upon material from earlier chapters. For example, problems in Chapter 3 that introduce numerical descriptive measures might also require development of appropriate charts or graphs taught in Chapter 2. In this way, students are continually reviewing and applying material learned in previous chapters, gaining a greater appreciation for how the different techniques fit together to provide an integrated set of business analysis tools.
Where appropriate, many of the Business Application Exercises include data sets requiring that they be analyzed using either Excel or Minitab. A special data set icon is used to distinguish these problems.
As a special feature, additional application problems and skill development exercises are located on the CD-ROM that accompanies the text.
We have included short cases at the end of each chapter. Like the Business Application Exercises, these cases are based on actual business situations. However, the cases are less directed and more open-ended than the Business Application problems and also require the students to integrate the statistical techniques covered in the chapter into the decision-making situation. The purpose of the cases is to give the students an opportunity to apply the tools and techniques they have learned to more loosely defined business problems, requiring them to identify key issues, apply relevant statistical techniques, draw conclusions, and provide reports detailing their findings.
REVISED TABLE OF CONTENTS
For the third edition, we have made some changes to the order in which the chapters are presented based on feedback we have had from reviewers and students and faculty who have used prior editions. For example, we have expanded our discussion of descriptive statistics and data presentation, since that aspect of the business statistics course is highly relevant to graduates in the workplace.
It is always a challenge to include all the topics that professors would like to see in a one-term business statistics textbook while at the same time keeping the text length to a manageable size. This is a special challenge to us since we have opted for a descriptive writing style with fully developed examples and applications. To help accomplish our objective in terms of topic coverage and presentation while staying within a manageable number of pages, the third edition includes a number of optional topics on the CD-ROM that accompanies the text. In addition, several complete chapters on topics not typically covered in a one-term course are included on the CD-ROM.
A variety of other special features are included in this text and the ancillary materials. These are briefly described below.
Accompanying the text is a CD-ROM with many special features including:
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Book Description Prentice Hall. Hardcover. Book Condition: New. 013093657X. Bookseller Inventory # AUD6861.1RGBR042616H0154
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