Statistics for Business and Economics

Dr. Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Business Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, he served on the faculty of the University of Cincinnati. He has also served as a visiting scholar at Stanford University and as a visiting Professor of Business Administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 40 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in numerous professional journals, including Science, Management Science, Operations Research and Interfaces. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing 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 Interfaces. In 2016, Dr. Camm received the George E. Kimball Medal for service to the operations research profession and in 2017 he was named an INFORMS Fellow. Thomas A. Williams is Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology (RIT). 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 first undergraduate programme in Information Systems. At RIT he was the first chair 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 elementary data analysis to the development of large-scale regression models. David R. Anderson is Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, 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. In addition, he was the coordinator of the colleges first executive programme. At the University of Cincinnati, Dr Anderso...

Book contents
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
Online contents
19 Index numbers
20 Statistical methods for quality control
21 Decision analysis
22 Sample surveys
Chapter Software Sections for EXCEL, MINITAB, SPSS and R
Appendix A: References and bibliography
Appendix B: Tables
Appendix C: Summation Notation
Appendix D: Answers to even-numbered exercises and fully worked solutions to exercises flagged with the SOLUTIONS icon.