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Business Analytics
Business Analytics

Business Analytics, 2nd Edition

ISBN10: 1264302800 | ISBN13: 9781264302802
By Sanjiv Jaggia, Alison Kelly, Kevin Lertwachara and Leida Chen
© 2023

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* The estimated amount of time this product will be on the market is based on a number of factors, including faculty input to instructional design and the prior revision cycle and updates to academic research-which typically results in a revision cycle ranging from every two to four years for this product. Pricing subject to change at any time.

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Business Analytics: Communicating with Numbers was written from the ground up to prepare students to understand, manage, and visualize the data, apply the appropriate tools, and communicate the findings and their relevance. Unlike other texts that simply repackage statistics and traditional operations research topics, this text seamlessly threads the topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive whole. It provides a holistic analytics process, including dealing with real life data that are not necessarily 'clean' and/or 'small' and stresses the importance of effectively communicating findings by including features such as a synopsis (a short writing sample) and a sample report (a longer writing sample) in every chapter. These features help students develop skills in articulating the business value of analytics by communicating insights gained from a non-technical standpoint.

Chapter 1: Introduction to Business Analytics

Chapter 2:  Data Management and Wrangling

Chapter 3:  Summary Measures

Chapter 4:  Data Visualization

Chapter 5:  Probability and Probability Distributions

Chapter 6:  Statistical Inference

Chapter 7:  Regression Analysis

Chapter 8:  More Topics in Regression Analysis

Chapter 9:  Logistic Regression

Chapter 10:  Forecasting with Time Series Data

Chapter 11:  Introduction to Data Mining

Chapter 12:  Supervised Data Mining: k-Nearest Neighbors and Naive Bayes

Chapter 13:  Supervised Data Mining: Decision Trees

Chapter 14:  Unsupervised Data Mining

Chapter 15:  Spreadsheet Modeling

Chapter 16:  Risk Analysis and Simulation

Chapter 17:  Optimization: Linear Programming

Chapter 18:  More Applications in Optimization 

Appendix A: Big Data Sets: Variable Description and Data Dictionary

Appendix B: Getting Started with Excel and Excel Add-Ins

Appendix C: Getting Started with R

Appendix D: Answers to Selected Exercises

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About the Author

Sanjiv Jaggia

Sanjiv Jaggia is a professor of economics and finance at California Polytechnic State University in San Luis Obispo. Dr. Jaggia holds a Ph.D. from Indiana University and is a Chartered Financial Analyst (CFA®). He enjoys research in statistics and data analytics applied to a wide range of business disciplines. Dr. Jaggia has published numerous papers in leading academic journals and has co-authored three successful textbooks, two in business statistics and one in business analytics. His ability to communicate in the classroom has been acknowledged by several teaching awards. Dr. Jaggia resides in San Luis Obispo with his wife and daughter. In his spare time, he enjoys cooking, hiking, and listening to a wide range of music. 

Alison Kelly

Alison Kelly is a professor of economics at Suffolk University in Boston. Dr. Kelly holds a Ph.D. from Boston College and is a Chartered Financial Analyst (CFA®). Dr. Kelly has published in a wide variety of academic journals and has co-authored three successful textbooks, two in business statistics and one in business analytics. Her courses in applied statistics and econometrics are popular with students as well as working professionals. She has also served as a consultant for a number of companies; her most recent work focused on how large financial institutions satisfy requirements mandated by the Dodd-Frank Act. Dr. Kelly resides in Hamilton, Massachusetts, with her husband, daughter, and son. In her spare time, she enjoys exercising and gardening. 

Kevin Lertwachara

Kevin Lertwachara is a professor of information systems at California Polytechnic State University in San Luis Obispo. Dr. Lertwachara holds a Ph.D. in Operations and Information Management from the University of Connecticut. Dr. Lertwachara’s research focuses on technology-based innovation, electronic commerce, health care informatics, and business analytics and his work has been published in scholarly books and leading academic journals. He teaches business analytics at both the undergraduate and graduate levels and has received several teaching awards. Dr. Lertwachara resides in the central coast of California with his wife and three sons. In his spare time, he coaches his sons’ soccer and futsal teams.

Leida Chen

Leida Chen is a professor of information systems at California Polytechnic State University in San Luis Obispo. Dr. Chen earned a Ph.D. in Management Information Systems from University of Memphis. His research and consulting interests are in the areas of business analytics, technology diffusion, and global information systems. Dr. Chen has published over 50 research articles in leading information systems journals, over 30 articles and book chapters in national and international conference proceedings and edited books, and a book on mobile application development. He teaches business analytics at both the undergraduate and graduate levels. In his spare time, Dr. Chen enjoys hiking, painting, and traveling with his wife and son to interesting places around the world.


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