Practical Business Statistics, Sixth Edition, is a conceptual, realistic, and matter-of-fact approach to managerial statistics that carefully maintains-but does not overemphasize-mathematical correctness. The book offers a deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results. The text uses excellent examples with real world data relating to the functional areas within Business such as finance, accounting, and marketing. It is well written and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details.
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Text packaged with CD including data sets, PowerPoint slides, StatPad software, and practice quizzes, combines all the students tools in one easy medium.
Excel incorporated throughout the text where appropriate. Excel integration is important to students who will utilize this software as practitioners.
Increased coverage of data collection. The reason data analysis is gaining favor is because it is closer to the way real people in real situations make decisions and solve problems.
Internet Exercises have been added; this gives students more exposure to the Internet as it relates to business statistics.
New, updated design, more appealing and attractive to students and instructors.
Updated selected exercises.
Emphasis on real business uses of statistics giving students a "real world" perspective.
Emphasis on basic understanding and interpretation rather than theory and computations providing a more applied approach to learning and teaching business statistics. The text delivers exactly what is business majors need to know and learn about statistics.
Easy to read style of presentation making learning statistics more exciting for students.
Problem sets that are practical diverse, believable and motivating from all functional areas of business to appeal to a wide variety of business students.
Liberal use of graphics and larger data sets which peaks student's interest.
Emphasis on topics such as regression, forecasting, quality, and data descriptions that are most often encountered in the business world. This gives students an understanding as to why these topics are important in business.
Key words section at the end of chapters and end of book glossary.
'Projects' section in the end-of-chapter material that brings statistics closer to students' needs and interests by asking them to define the problem and choose the data set from their own interests.
Brief, illustrative case studies offer students practice in business decision-making and problem solving.
Andrew F. Siegel holds the Grant I. Butterbaugh Professorship in Quantitative Methods and Finance at the Michael G. Foster School of Business, University of Washington, Seattle, and is also Adjunct Professor in the Department of Statistics. His Ph.D. is in statistics from Stanford University (1977). Before settling in Seattle, he held teaching and/ or research positions at Harvard University, the University of Wisconsin, the RAND Corporation, the Smithsonian Institution, and Princeton University. He has taught statistics at both undergraduate and graduate levels, recently earning Excellence in Teaching Awards for Executive MBA statistics instruction, 2013, and 2014. The interest-rate model he developed with Charles Nelson (the Nelson-Siegel Model) is in use at central banks around the world. His work has been translated into Chinese and Russian. His articles have appeared in many publications, including the Journal of the American Statistical Association, the Encyclopedia of Statistical Sciences, the American Statistician, Proceedings of the National Academy of Sciences, Nature, the American Mathematical Monthly, the Journal of the Royal Statistical Society, the Annals of Statistics, the Annals of Probability, the Society for Industrial and Applied Mathematics Journal on Scientific and Statistical Computing, Statistics in Medicine, Biometrika, Biometrics, Statistical Applications in Genetics and Molecular Biology, Mathematical Finance, and the Journal of Applied Probability.
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