Essentials of Business Analytics, 2nd Edition

Author Biography

James J. Cochran is Professor of Applied Statistics and the Rogers-Spivey Faculty Fellow in the Department of Information Systems, Statistics and Management Science at the University of Alabama. Prior to joining the University of Alabama faculty, Dr. Cochran was Professor of Quantitative Analysis and the Bank of Ruston, Barnes, Thompson, & Thurman Endowed Research Professor at Louisiana Tech University. He has been a visiting scholar at Stanford University, Universidad de Talca, and the University of South Africa. Professor Cochran has published over two dozen 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, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, JOURNAL OF COMBINATORIAL OPTIMIZATION, and other professional journals. He received the 2008 INFORMS Prize for the Teaching of Operations Research Practice and the 2010 Mu Sigma Rho Statistical Education Award. Professor Cochran was elected to the International Statistics Institute in 2005 and named a Fellow of the American Statistical Association in 2011. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, he has organized and chaired teaching effectiveness workshops in Uruguay, South Africa, Colombia, India, Argentina, Kenya, Cameroon, and Croatia. He has served as a statistics and operations research consultant to numerous companies and not-for-profit organizations. He served as editor-in-chief of INFORMS TRANSACTIONS ON EDUCATION from 2007 to 2012, and is on the editorial board of INTERFACES, the JOURNAL OF QUANTITATIVE ANALYSIS IN SPORTS, and ORION. He holds a BS, MS, and MBA from Wright State University and a PhD from the University of Cincinnati. Dr. Jeffrey D. Camm is Professor of Quantitative Analysis and head of the Department of Quantitative Analysis and Operations Management at the University of Cincinnati, where he has been since 1984. He also has served as 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 more than 30 papers in the general area of optimization applied to problems in operations management, and his research has been funded by the Air Force Office of Scientific Research, The Office of Naval Research, and the U.S. Department of Energy. Among his honors, he was named the Dornoff Fellow of Teaching Excellence and received the 2006 INFORMS Prize for the Teaching of Operations Research Practice. Dr. Camm currently serves as editor-in-chief of INTERFACES and is on the editorial board of INFORMS TRANSACTIONS ON EDUCATION. He received his PhD in Management Science from Clemson University.

Table of Contents

1. Introduction
2. Descriptive Statistics.
3. Data Visualization.
4. Descriptive Data Mining.
5. Probability: An Introduction to Modeling Uncertainty.
6. Statistical Inference.
7. Linear Regression.
8. Time Series Analysis and Forecasting.
9. Predictive Data Mining.
10. Spreadsheet Models.
11. Linear Optimization Models.
12. Integer Linear Optimization Models.
13. Nonlinear Optimization Models.
14. Monte Carlo Simulation.
15. Decision Analysis. Appendix A: Basics of Excel. Appendix B: Database Basics with Microsoft Access. Appendix C: Solutions to Even-Numbered Questions (online).

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