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Essentials of Business Analytics

Essentials of Business Analytics

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Develop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 5E. You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills. Real examples and memorable visuals clearly illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R or the Python-based Orange data mining software to perform advanced analytics. Practical, relevant problems at all levels of difficulty let you apply what you've learned. Updates throughout this edition address topics beyond traditional quantitative concepts, such as data wrangling, data visualization and data mining, which are increasingly important in today's business environment. MindTap and WebAssign online learning platforms are also available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations to strengthen your understanding of key concepts.

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About the Book

ESSENTIALS OF BUSINESS ANALYTICS provides coverage over the full range of analytics--descriptive, predictive, prescriptive--not covered by any other single book. It includes step-by-step instructions to help students learn how to use Excel and powerful but easy to use Excel add-ons such as XL Miner for data mining and Analytic Solver Platform for optimization and simulation.

About the Author

Jeffrey D. Camm 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. James J. Cochran 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. Michael J. Fry Dr. Michael J. Fry is Associate Professor and Lindner Research Fellow in the Department of Operations, Business Analytics, and Information Systems in the Carl H. Lindner College of Business at the University of Cincinnati, where he also serves as Assistant Director for the Center for Business Analytics. At the University of Cincinnati since 2002, he has been a visiting professor at the Samuel Curtis Johnson Graduate School of Management at Cornell University and the Sauder School of Business at the University of British Columbia. Dr. Fry has published more than twenty research publications in such journals as OPERATIONS RESEARCH, M&SOM, TRANSPORTATION SCIENCE, NAVAL RESEARCH LOGISTICS, IIE TRANSACTIONS, and INTERFACES. His research interests include applying management science methods to the areas of supply chain analytics, sports analytics, and public policy operations. He has worked with many different organizations for his research, Including Dell, Inc., Copeland Corporation, Starbucks Coffee Company, The Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals, and the Cincinnati Zoo and Botanical Gardens. Professor Fry's teaching awards include the 2013 Michael L. Dean Excellence in Graduate Teaching Award and the 2006 Daniel J. Westerbeck Junior Faculty Teaching Award. Born in Killeen, Texas, he earned a B.S. from Texas A&M University, and M.S.E. and Ph.D. degrees from the University of Michigan. Jeffrey W. Ohlmann Jeffrey W. Ohlmann is Associate Professor of Management Sciences in the Tippie College of Business at the University of Iowa, where he has been since 2003. Professor Ohlmann's research on the modeling and solution of decision-making problems has produced more than a dozen research papers in such journals as MATHEMATICS OF OPERATIONS RESEARCH, INFORMS JOURNAL ON COMPUTING, TRANSPORTATION SCIENCE, and INTERFACES. He has collaborated with companies such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections and the Cincinnati Bengals. Due to the relevance of his work to industry, he received the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice. Born in Valentine, Nebraska, he earned a BS from the University of Nebraska and MS and PhD degrees from the University of Michigan. David R. Anderson Dr. David R. Anderson is a textbook author and Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He has served as head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. He was also coordinator of the College's first Executive Program. In addition to introductory statistics for business students, Dr. Anderson has taught graduate-level courses in regression analysis, multivariate analysis, and management science. He also has taught statistical courses at the Department of Labor in Washington, D.C. Professor Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the coauthor of ten textbooks related to decision sciences and actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, he earned his BS, MS, and PhD degrees from Purdue University. Dennis J. Sweeney Dr. Dennis J. Sweeney is a textbook author, Professor Emeritus of Quantitative Analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, he has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor Sweeney has published more than 30 articles 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. Dr. Sweeney is the coauthor of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a BS degree from Drake University, graduating summa cum laude. He received his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow. Thomas A. Williams Dr. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology where 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. 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. The co-author of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics, Professor Williams 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. He earned his B.S. degree at Clarkson University and completed his graduate work at Rensselaer Polytechnic Institute, where he received his M.S. and Ph.D. degrees.



Table of Contents:
1. What Is Business Analytics? 2. Descriptive Statistics. 3. Data Visualization. 4. Linear Regression. 5. Time Series Analysis and Forecasting. 6. Data Mining. 7. Spreadsheet Models. 8. Linear Optimization Models. 9. Integer Linear Optimization. 10. Nonlinear Optimization Models. 11. Monte Carlo Simulation. 12. Decision Analysis. Appendix A: Basics of Excel. Appendix B: Data Management and Microsoft Access.


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Product Details
  • ISBN-13: 9788131527658
  • Publisher: Cengage Learning India Pvt.Ltd.
  • Publisher Imprint: South Western
  • Edition: 1
  • Language: English
  • Width: 203 mm
  • ISBN-10: 8131527654
  • Publisher Date: April, 2015
  • Binding: Paperback
  • Height: 254 mm
  • No of Pages: 700

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