
Business Analytics ISE
McGraw-Hill Education (Publisher)
2nd Edition
Will be published approx. on 8. March 2022
Book
Paperback/Softback
1600 pages
978-1-265-08768-5 (ISBN)
Description
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.
More details
Edition
2nd edition
Language
English
Place of publication
OH
United States
Target group
College/higher education
US School Grade: From College Freshman to College Graduate Student
Illustrations
167 Illustrations
Dimensions
Height: 274 mm
Width: 216 mm
Thickness: 36 mm
Weight
1291 gr
ISBN-13
978-1-265-08768-5 (9781265087685)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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 (R)). 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 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 (R)). 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 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 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.
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 (R)). 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 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 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.
Content
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: Introduction to Data Mining
CHAPTER 9: More Topics in Regression Analysis
CHAPTER 10: Logistic Regression Models
CHAPTER 11: Supervised Data Mining: kNN and Naive Bayes
CHAPTER 12: Supervised Data Mining: Decision Trees
CHAPTER 13: Unsupervised Data Mining
CHAPTER 14: Forecasting with Time Series Data
CHAPTER 15: Spreadsheet Modelling
CHAPTER 16: Risk and Simulation
CHAPTER 17: Optimization: Linear Programming
CHAPTER 18: Optimization: Integer and Nonlinear Programming
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 Statistical Tables
APPENDIX E Answers to Selected Exercises
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: Introduction to Data Mining
CHAPTER 9: More Topics in Regression Analysis
CHAPTER 10: Logistic Regression Models
CHAPTER 11: Supervised Data Mining: kNN and Naive Bayes
CHAPTER 12: Supervised Data Mining: Decision Trees
CHAPTER 13: Unsupervised Data Mining
CHAPTER 14: Forecasting with Time Series Data
CHAPTER 15: Spreadsheet Modelling
CHAPTER 16: Risk and Simulation
CHAPTER 17: Optimization: Linear Programming
CHAPTER 18: Optimization: Integer and Nonlinear Programming
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 Statistical Tables
APPENDIX E Answers to Selected Exercises