Practical Business Statistics

Siegel, Andrew F. (Professor of Information Systems and Operations Management, Professor of Finance and Business Economics, and Adjunct Professor of Statistics, Foster School of Business, University of Washington, Seattle, WA, USA)|Wagner, Michael R. (As

ISBN 10: 0128200251 / ISBN 13: 9780128200254

Published by Elsevier Science Publishing Co Inc, 2022

About this Item

&Uumlber den AutorrnrnAndrew 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 Departm.

Seller Inventory # 510111020

Bibliographic Details

• Title: Practical Business Statistics
• Publisher: Elsevier Science Publishing Co Inc
• Publication Date: 2022
• Language: English
• ISBN 10: 0128200251
• ISBN 13: 9780128200254
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Practical Business Statistics, Eighth Edition, offers readers a practical, accessible approach to managerial statistics that carefully maintains, but does not overemphasize mathematical correctness. The book fosters deep understanding of both how to learn from data and how to deal with uncertainty, while promoting the use of practical computer applications. This trusted resource 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 business sector functional areas such as finance, accounting, and marketing. Written in an engaging style, this timely revision is class-tested and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details.

• Provides users with a conceptual, realistic, and matter-of-fact approach to managerial statistics
• Offers an accessible approach to teach present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand concepts and to interpret results
• Features updated examples and images to illustrate important applied uses and current business trends
• Includes robust ancillary instructional materials such as an instructor’s manual, lecture slides, and data files

About the Authors

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, and earned seven teaching awards in 2015 and 2016. 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, Contemporary Accounting Research, the Journal of Finance, and the Journal of Applied Probability.

Michael R. Wagner is an Associate Professor of Operations Management and a Neal and Jan Dempsey Endowed Faculty Fellow at the Michael G. Foster School of Business, University of Washington, Seattle. His Ph.D. is in Operations Research from MIT (2006). He has taught data analytics at both undergraduate and graduate levels, and earned the Ron Crockett Award for Innovation in Education (2014). His articles have appeared in many publications, including the journals Management Science, Operations Research, Manufacturing & Service Operations Management, Mathematics of Operations Research, Mathematical Programming, IIE Transactions, European Journal of Operational Research, Operations Research Letters, Networks, Computers & Operations Research, and Transportation Science.