Business Analytics / Edition 2

by James Evans

Overview

Business Analytics, Second Edition teaches the fundamental concepts of the emerging field of business analytics and provides vital tools in understanding how data analysis works in today’s organizations. Students will learn to apply basic business analytics principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. Included access to commercial grade analytics software gives students real-world experience and career-focused value. Author James Evans takes a balanced, holistic approach and looks at business analytics from descriptive, and predictive perspectives.

KEY TOPICS: Foundations of Business Analytics; Introduction to Business Analytics; Analytics on Spreadsheets; Descriptive Analytics; Visualizing and Exploring Data; Descriptive Statistical Measures; Probability Distributions and Data Modeling; Sampling and Estimation; Statistical Inference; Predictive Analytics; Trendlines and Regression Analysis; Forecasting Techniques; Introduction to Data Mining; Spreadsheet Modeling and Analysis; Monte Carlo Simulation and Risk Analysis; Prescriptive Analytics; Linear Optimization; Applications of Linear Optimization; Integer Optimization; Decision Analysis

MARKET: For all readers interested in business analytics.

Product Details

ISBN-13:	9780321997821
Publisher:	Pearson Education
Publication date:	12/30/2014
Edition description:	Older Edition
Pages:	664
Product dimensions:	7.80(w) x 9.80(h) x 0.90(d)

About the Author

James R. Evans

Professor, University of Cincinnati College of Business

James R. Evans is professor in the Department of Operations, Business Analytics, and Information Systems in the College of Business at the University of Cincinnati. He holds BSIE and MSIE degrees from Purdue and a PhD in Industrial and Systems Engineering from Georgia Tech.

Dr. Evans has published numerous textbooks in a variety of business disciplines, including statistics, decision models, and analytics, simulation and risk analysis, network optimization, operations management, quality management, and creative thinking. He has published over 90 papers in journals such as Management Science, IIE Transactions, Decision Sciences, Interfaces, the Journal of Operations Management, the Quality Management Journal, and many others, and wrote a series of columns in Interfaces on creativity in management science and operations research during the 1990s. He has also served on numerous journal editorial boards and is a past-president and Fellow of the Decision Sciences Institute. In 1996, he was an INFORMS Edelman Award Finalist as part of a project in supply chain optimization with Procter & Gamble that was credited with helping P&G save over $250,000,000 annually in their North American supply chain, and consulted on risk analysis modeling for Cincinnati 2012’s Olympic Games bid proposal.

A recognized international expert on quality management, he served on the Board of Examiners and the Panel of Judges for the Malcolm Baldrige National Quality Award. Much of his current research focuses on organizational performance excellence and measurement practices.

Table of Contents

Brief Contents

Preface

About the Author

PART 1: Foundations of Business Analytics

1. Introduction to Business Analytics

2. Analytics on Spreadsheets

Part 2: Descriptive Analytics

3. Visualizing and Exploring Data

4. Descriptive Statistical Measures

5. Probability Distributions and Data Modeling

6. Sampling and Estimation

7. Statistical Inference

Part 3: Predictive Analytics

8. Trendlines and Regression Analysis

9. Forecasting Techniques

10. Introduction to Data Mining

11. Spreadsheet Modeling and Analysis

12. Monte Carlo Simulation and Risk Analysis

Part 4: Prescriptive Analytics

13. Linear Optimization

14. Applications of Linear Optimization

15. Integer Optimization

16. Decision Analysis

Supplementary Chapter A (online): Nonlinear and Non-Smooth Optimization

Supplementary Chapter B (online): Optimization Models with Uncertainty

Appendix A

Glossary

Index