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Statistics for Business and Economics, 6th Edition

David Anderson, Dennis J. Sweeney, Thomas Williams, Jeffrey D. Camm, James J. Cochran, James Freeman, Eddie Shoesmith

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Starting At £35.00 See pricing and ISBN options
Statistics for Business and Economics 6th Edition by David Anderson/Dennis J. Sweeney/Thomas Williams/Jeffrey D. Camm/James J. Cochran/James Freeman/Eddie Shoesmith

Overview

With the non-mathematician in mind, the sixth edition of Statistics for Business and Economics teaches learners the key concepts of statistics in business, management and economics. The authors blend statistical methodology with applications of data analysis to illustrate the fundamental role of statistics in problem-solving and decision making.

Computational methods give students a solid foundation to master statistical application and interpretation. At the end of each section, practical exercises encourage conceptual understanding of real-world problems. New content on big data enriches the learning experience and prepares students for the workplace.

David Anderson

David R. Anderson is Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He earned his BS, MS and PhD degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration at the University of Cincinnati. In addition, he was the coordinator of the College’s first Executive Program. At the University of Cincinnati, Professor Anderson has taught introductory statistics for business students as well as graduate-level courses in regression analysis, multivariate analysis and management science. He has also taught statistical courses at the Department of Labor in Washington, D.C. He has been honoured with nominations and awards for excellence in teaching and excellence in service to student organizations. Professor Anderson has co-authored 10 textbooks in the areas of statistics, management science, linear programming and production and operations management. He is an active consultant in the field of sampling and statistical methods.

Dennis J. Sweeney

Dennis J. Sweeney is Professor Emeritus of Quantitative Analysis and Founder of the Center for Productivity Improvement at the University of Cincinnati. He earned a BSBA degree from Drake University and his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow. Professor Sweeney has worked in the management science group at Procter & Gamble and spent a year as a visiting professor at Duke University. Professor Sweeney served as Head of the Department of Quantitative Analysis and as Associate Dean of the College of Business Administration at the University of Cincinnati. Professor Sweeney has published more than 30 articles and monographs in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences and other journals. Professor Sweeney has co-authored 10 textbooks in the areas of statistics, management science, linear programming and production and operations management.

Thomas Williams

Thomas A. Williams is Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology. Born in Elmira, New York, he earned his BS degree at Clarkson University. He did his graduate work at Rensselaer Polytechnic Institute, where he received his MS and PhD degrees. Before joining the College of Business at RIT, Professor Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed the undergraduate program in Information Systems and then served as its coordinator. At RIT he was the first chairman of the Decision Sciences Department. He teaches courses in management science and statistics, as well as graduate courses in regression and decision analysis. Professor Williams is the co-author of 11 textbooks in the areas of management science, statistics, production and operations management and mathematics. He has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models.

Jeffrey D. Camm

Jeffrey D. Camm is the Inmar Presidential Chair and Senior Associate Dean of Analytics in the School of Business at Wake Forest University. He holds a BS from Xavier University (Ohio) and a PhD from Clemson University. Prior to joining the faculty at Wake Forest, he was on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published over 45 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, Interfaces and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the recipient of the 2006 INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practising what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010, he served as editor-in-chief of INFORMS Journal of Applied Analytics (formerly Interfaces). In 2017, he was named an INFORMS Fellow.

James J. Cochran

James J. Cochran is Professor of Applied Statistics, the Rogers-Spivey Faculty Fellow and Associate Dean for Faculty and Research at the University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S., and M.B.A. degrees from Wright State University and his Ph.D. from the University of Cincinnati. Dr. Cochran has served at The University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 45 papers in the development and application of operations research and statistical methods. He has published his research in Management Science, The American Statistician, Communications in Statistics-Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, INFORMS Journal of Applied Analytics and Statistics and Probability Letters. He was the 2008 recipient of the INFORMS Prize for the Teaching of Operations Research Practice and the 2010 recipient of the Mu Sigma Rho Statistical Education Award. Dr. Cochran was elected to the International Statistics Institute in 2005 and named a fellow of the American Statistical Association in 2011. He received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In 2017 he received the American Statistical Association’s Waller Distinguished Teaching Career Award and was named a fellow of INFORMS. In 2018 he received the INFORMS President’s Award. A strong advocate for effective statistics and operations research education as a means of improving the quality of applications to real problems, Dr. Cochran has organized and chaired teaching workshops throughout the world.

James Freeman

James Freeman is formerly Senior Lecturer in Statistics and Operational Research at Alliance Manchester Business School (AMBS), UK. After taking a first degree in Pure Mathematics at UCW Aberystwyth, he went on to receive MSc and PhD degrees in Applied Statistics from Bath and Salford Universities, respectively. In 1992/3 he was visiting professor at the University of Alberta. Before joining AMBS, he was Statistician at the Distributive Industries Training Board – and prior to that – the Universities Central Council on Admissions. He has taught undergraduate and postgraduate courses in business statistics and operational research courses to students from a wide range of management and engineering backgrounds. Until 2017, he taught the statistical core course on AMBS’s Business Analytics masters programme – since rated top in Europe and sixth in the world. For many years he was also responsible for providing introductory statistics courses to staff and research students at the University of Manchester’s Staff Teaching Workshop. Through his gaming and simulation interests, he has been involved in a significant number of external consultancy and grant-aided projects. This culminated in his receiving significant government (‘KTP’) funding for research in the area of risk management in 2012. Between July 2008 and December 2014, he was Editor of the Operational Research Society’s OR Insight journal and between 2018 and 2020 was Editor of the Tewkesbury Historical Society Bulletin. In November 2012, he received the Outstanding Achievement Award at the Decision Sciences Institutes 43rd Annual Meeting in San Francisco. In 2018 he was awarded an Honorary Fellowship by the University of Manchester.

Eddie Shoesmith

Eddie Shoesmith is a Fellow of the University of Buckingham, UK, where he was formerly Senior Lecturer in Statistics. Born and brought up in the West Riding of Yorkshire, he was awarded an MA (Natural Sciences) at the University of Cambridge and a BPhil (Economics and Statistics) at the University of York. Prior to his 35 years at Buckingham, Eddie worked as a statistician and researcher for the UK Government Statistical Service and for the London Boroughs of Hammersmith and Haringey. During his Buckingham career, he held posts, at various times, as Dean of Sciences, as Head of Psychology and as Programme Director for undergraduate business and management programmes. He has taught introductory and intermediate-level applied statistics courses to undergraduate and postgraduate student groups in a wide range of disciplines: business and management, economics, accounting, psychology, biology and social sciences. He has also taught statistics to social and political sciences undergraduates at the University of Cambridge and has held external examiner posts at the Universities of Cranfield and Hertfordshire. Now retired from full-time academic life, Eddie contributes as an Associate Lecturer in the School of Leadership & Management, the School of Computing & IT and the School of Digital Finance at the University of Arden.
  • DIGITAL ONLY: New content on big data enriches students’ understanding of how this exciting topic intertwines with statistics and decision making.
  • DIGITAL ONLY: New content on data visualization offers a broader introduction to the importance of presenting data meaningfully in a business context.
  • 77 updated exercise questions sustain students’ progress by providing new and up-to-date challenges.
  • A Statistics in Practice feature introduces each chapter to immediately illustrate the real-life function of statistics.
  • Real-life case problems at the end of each chapter link the theory to the real world.
  • Exercise questions at the end of each section allow students to regularly check their knowledge and progress.
  • Data files suitable for SPSS, Excel and R accompany exercises, examples and Case Problems.
  • WebAssign is available with this title, which is a digital solution designed by educators to enhance the teaching and learning experience. WebAssign provides extensive content, instant assessment and unfailing support.
  • A companion website is available with more exercises and solutions, appendices, data sets, online chapters, sample papers and software sections, covering key functions in Excel, SPSS and R as well as PowerPoint slides and a Solutions Manual for lecturers.
  • New Statistics in Practice and Case Problem features highlight the importance of statistics in business and allow students to fully grasp the practicalities of the topics.
Preface
Acknowledgements
About the authors
1. Data and Statistics
2. Descriptive statistics: tabular and graphical presentations
3. Descriptive statistics: numerical measures
4. Introduction to probability
5. Discrete probability distributions
6. Continuous probability distributions
7. Sampling and sampling distributions
8. Interval estimation
9. Hypothesis tests
10. Statistical inference about means and proportions with two populations
11. Inferences about population variances
12. Tests of goodness of fit and independence
13. Experimental design and analysis of variance
14. Simple linear regression
15. Multiple regression
16. Regression analysis: model building
17. Time series analysis and forecasting
18. Non-parametric methods
Appendix A References and bibliography
Appendix B Tables
Glossary
Credits
Index
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The new sixth edition of Statistics for Business and Economics is available with WebAssign, an online learning platform designed by educators to enhance the teaching and learning experience. WebAssign is fully customizable and provides extensive content, instant assessment and unfailing support. Additionally, a comprehensive companion website is available for instructors with further exercises and solutions, appendices, data sets, online chapters, sample papers and software sections, covering key functions in Excel, SPSS and R as well as PowerPoint slides and a Solutions Manual for lecturers.

eTextbook: Statistics for Business and Economics

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