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Essential Business Analytics, 3rd Edition
by Jeffrey D. Camm (Author), James J. Cochran (Author), Michael J. Fry (Author), Jeffrey W. Ohlmann (Author), David R. Anderson (Author), Dennis J. Sweeney (Author), Thomas A. Williams (Author)
Build valuable skills that are in high demand in today's businesses with BUSINESS ANALYTICS, 3E. You master the full range of analytics as you strengthen your descriptive, predictive and prescriptive analytic skills. Real-world examples and visuals help illustrate data and results for each topic. Clear, step-by-step instructions for various software programs, including Microsoft Excel, Analytic Solver, and JMP Pro, teach you how to perform the analyses discussed. Practical, relevant problems at all levels of difficulty further help you apply what you've learned to succeed in your course.
This textbook contains one of the first collections of materials that are essential to the growing field of business analytics. In Chapter 1 the book presents an overview of business analytics and our approach to the material in this textbook. In simple terms, business analytics helps business professionals make better decisions based on data. The book discusses models for summarizing, visualizing, and understanding useful information from historical data in Chapters 2 through 6. Chapters 7 through 9 introduce methods for both gaining insights from historical data and predicting possible future outcomes. Chapter 10 covers the use of spreadsheets for examining data and building decision models. In Chapter 11, the book demonstrates how to explicitly introduce uncertainty into spreadsheet models through the use of Monte Carlo simulation. In Chapters 12 through 14 the book discusses optimization models to help decision makers choose the best decision based on the available data. Chapter 15 is an overview of decision analysis approaches for incorporating a decision maker’s views about risk into decision making. In Appendix A the book presents optional material for students who need to learn the basics of using Microsoft Excel. The use of databases and manipulating data in Microsoft Access is discussed in Appendix B.
This textbook can be used by students who have previously taken a course on basic statistical methods as well as students who have not had a prior course in statistics. Business Analytics 3E is also amenable to a two-course sequence in business statistics and analytics. All statistical concepts contained in this textbook are presented from a business analytics perspective using practical business examples. Chapters 2, 5, 6, and 7 provide an introduction to basic statistical concepts that form the foundation for more advanced analytics methods. Chapters 3, 4, and 9 cover additional topics of data visualization and data mining that are not traditionally part of most introductory business statistics courses, but they are exceedingly important and commonly used in current business environments. Chapter 10 and Appendix A provide the foundational knowledge students need to use Microsoft Excel for analytics applications. Chapters 11 through 15 build upon this spreadsheet knowledge to present additional topics that are used by many organizations that are leaders in the use of prescriptive analytics to improve decision making.
Brief Contents
CHAPTER 1 Introduction 2
CHAPTER 2 Descriptive Statistics 18
CHAPTER 3 Data Visualization 82
CHAPTER 4 Descriptive Data Mining 138
CHAPTER 5 Probability: An Introduction to Modeling Uncertainty 166
CHAPTER 6 Statistical Inference 220
CHAPTER 7 Linear Regression 294
CHAPTER 8 Time Series Analysis and Forecasting 372
CHAPTER 9 Predictive Data Mining 422
CHAPTER 10 Spreadsheet Models 464
CHAPTER 11 Monte Carlo Simulation 500
CHAPTER 12 Linear Optimization Models 556
CHAPTER 13 Integer Linear Optimization Models 606
CHAPTER 14 Nonlinear Optimization Models 646
CHAPTER 15 Decision Analysis 678
APPENDIX A Basics of Excel 724
APPENDIX B Database Basics with Microsoft Access 736
APPENDIX C Solutions to Even-Numbered Questions (MindTap Reader)
REFERENCES 774
INDEX 776
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