Designed for the one-term MBA or undergraduate introduction to business statistics course, this text places emphasis on data and the common techniques and methods used to analyze them in business. It introduces concepts using practical examples and illustrates them with computer output from MINITAB™, Microsoft Excel, and JMP. The book integrates a business decision-making case into each chapter for motivational and illustration purposes and includes a business case assignment at the end of each chapter. These cases revolve around realistic business settings with realistic data sets that put students in the role of managers who need to make business decisions based on data. Review problems requiring students to use previously learned concepts also appear throughout to promote understanding of the relationships among statistical methods.
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The late David Hildebrand earned his Ph.D. at Carnegie-Mellon University, and was affiliated with the Wharton School of Business at the University of Pennsylvania.
Lyman Ott earned his Bachelor's degree in Mathematics and Education and Master's degree in Mathematics from Bucknell University, and Ph.D in Statistics from the Virginia Polytechnic Institute. After two years working in statistics in the pharmaceutical industry, Dr. Ott became assistant professor in the Statistic Department at the University of Florida in 1968 and was named associate professor in 1972. He joined Merrell-National laboratories in 1975 as head of the Biostatistics Department and then head of the company's Research Data Center. He later became director of Biomedical Information Systems, Vice President of Global Systems and Quality Improvement in Research and Development, and Senior Vice President Business Process Improvement and Biometrics. He retired from the pharmaceutical industry in 1998, and now serves as consultant and Board of Advisors member for Abundance Technologies, Inc. Dr. Ott has published extensively in scientific journals and authored or co-authored seven college textbooks including Basic Statistical Ideas for Managers, Statistics: A Tool for the Social Sciences and An Introduction to Statistical Methods and Data Analysis. He has been a member of the Industrial Research Institute, the Drug Information Association and the Biometrics Society. In addition, he is a Fellow of the American Statistical Association and received the Biostatistics Career Achievement Award from the Pharmaceutical research and Manufacturers of America in 1998. He was also an All-American soccer player in college and is a member of the Bucknell University Athletic Hall of Fame.
J. Brian Gray is Professor of Statistics in the Applied Statistics Program and in the Department of Information Systems, Statistics, and Management Science at The University of Alabama, where he teaches a variety of statistics courses at the undergraduate, masters, and doctoral levels. Dr. Gray has taught MBA and Executive MBA statistics courses for the past 20 years and has received several teaching awards from the MBA and Executive MBA Associations of The University of Alabama and Texas Christian University. He co-authored the book BUSINESS CASES IN STATISTICAL DECISION-MAKING: COMPUTER BASED APPLICATIONS. Dr. Gray is an active member of the American Statistical Association. His current research interests are in the areas of applied statistics, exploratory data analysis, data mining, regression analysis, statistical computing, and graphics. He has published research articles in journals including TECHNOMETRICS, JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, THE AMERICAN STATISTICIAN, COMPUTATIONAL STATISTICS AND DATA ANALYSIS, JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, STATISTICS AND COMPUTING, JOURNAL OF REAL ESTATE RESEARCH, and JOURNAL OF BUSINESS, FINANCE, & ACCOUNTING. Dr. Gray received the Wilcoxon Prize for Best Practical Application Paper in TECHNOMETRICS in 1984.
"This book is excellent overall in terms of topics covered, clarity and organization, reasonable brevity (necessary for shorter courses), great examples of statistical output from a many different types of statistical software, and the degree to which it illustrates a wide range of business applications. It also serves as a great reference for students after the introductory course is over. I think it superior to its competitors on these dimensions."
"What do you view to be the three key strengths of the text? Clear and lucid explanation of key concepts. Brevity and conciseness of treatment - a systematic and structured approach to explaining the concepts well, and thereby not testing student patience! The overall organization of the text in terms of the Definition Boxes, Example Boxes, Summary of key concepts at the start of each chapter, and overall flow of topics."
"What do you view to be the three key strengths of the text? Its inclusion of a fair number of modeling problems, its math level (more mature than college algebra), and its coverage of regression."
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