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ISBN10: 126692602X | ISBN13: 9781266926020
Business Analytics
ISBN10: 126692602X
ISBN13: 9781266926020
By Sanjiv Jaggia, Alison Kelly, Kevin Lertwachara and Leida Chen
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126692602X |
ISBN13: 9781266926020
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ISBN10:
1265867674 |
ISBN13: 9781265867676
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- Unbound loose-leaf version of full text
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ISBN10:
1265909296 |
ISBN13: 9781265909291
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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.
Business Analytics: Communicating with Numbers prepares students for the data-driven demands of today’s business world by equipping them with essential skills in data analysis, visualization, and communication. It offers a comprehensive, hands-on approach to business analytics, covering everything from data wrangling to predictive and prescriptive analytics. Through real-world case studies and experiential learning, students work with Excel, R, and Python to tackle real-life data challenges. The focus on data storytelling ensures students can effectively communicate insights to diverse stakeholders. With expanded coverage of big data, text mining, and data mining, this title readies students for career success in a rapidly evolving field.
1. Introduction to Business Analytics
2. Data Management and Wrangling
3. Summary Measures
4. Data Visualization
5. Probability and Probability Distributions
6. Statistical Inference
7. Regression Analysis
8. More Topics in Regression Analysis
9. Logistic Regression
10. Forecasting with Time Series Data
11. Introduction to Data Mining
12. Supervised Data Mining: k-Nearest Neighbors and Naïve Bayes
13. Supervised Data Mining: Decision Trees
14. Unsupervised Data Mining
15. Spreadsheet Modeling
16. Risk Analysis and Simulation
17. Optimization: Linear Programming
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: Getting Started with Python
APPENDIX E: Answers to Selected Exercises
2. Data Management and Wrangling
3. Summary Measures
4. Data Visualization
5. Probability and Probability Distributions
6. Statistical Inference
7. Regression Analysis
8. More Topics in Regression Analysis
9. Logistic Regression
10. Forecasting with Time Series Data
11. Introduction to Data Mining
12. Supervised Data Mining: k-Nearest Neighbors and Naïve Bayes
13. Supervised Data Mining: Decision Trees
14. Unsupervised Data Mining
15. Spreadsheet Modeling
16. Risk Analysis and Simulation
17. Optimization: Linear Programming
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: Getting Started with Python
APPENDIX E: Answers to Selected Exercises
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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