Author(s): Luiz Paulo Favero (Author), Patricia Belfiore (Author)
Publisher: Academic Press
Publication Date: 7 Jun. 2019
Language: English
Print length: 1244 pages
ISBN-10: 0128112166
ISBN-13: 9780128112168
Book Description
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®.
Combines statistics and operations research modeling to teach the principles of business analytics
Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business
Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs
Editorial Reviews
Review
“Data Science for Business and Decision Making brings together the key topics required as the foundation for understanding and applying analytics for decision making. The authors have carefully selected the topics, and each one is clearly explained, described, and reinforced with a diverse set of exercises.” –Rahul Saxena, Cobot Systems
“Data Science for Business and Decision Making provides a thorough essay about statistical methods which are commonly used in business without requiring a strong mathematical background. The presentation is rigorous and accessible thanks to a large number of examples that are developed step-by-step. The illustrations feature various software and the proposed exercises are particularly helpful for students and practitioners.” –Francesco Bartolucci, University of Perugia
Review
Combines statistics and operations research to teach business analytics to those who want to apply quantitative methods in their work
From the Back Cover
Tangible competitive advantages can emerge from vast amounts of complex data translated into clear and manageable information. Data Science for Business and Decision Making covers both Statistics and Operations Research, while most competing textbooks focus on one or the other. As a result, it more clearly defines the principles of Business Analytics for those with backgrounds in business who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization, and simulation for practitioners of Business Analytics. Each of its chapters uses the same didactic format followed by exercises with answers at the back of the book. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, IBM SPSS Statistics Software®, and R.
About the Author
Dr. Fávero is a Full Professor at the Economics, Business Administration and Accounting College and at the Polytechnic School of the University of Sao Paulo (FEAUSP and EPUSP), where he teaches Data Science, Data Analysis, Multivariate Modeling, Machine and Deep Learning and Operational Research to undergraduate, Master’s and Doctorate students. He has a Post-Doctorate degree in Data Analysis and Econometrics from Columbia University in New York. He is a tenured Professor by FEA/USP (with greater focus on Quantitative Modeling). He has a degree in Engineering from USP Polytechnic School, a post-graduate degree in Business Administration from Getúlio Vargas Foundation (FGV/SP), and he has received the titles of Master and PhD in Data Science and Quantitative Methods applied to Organizational Economics from FEA/USP. He is a Visiting Professor at the Federal University of Sao Paulo (UNIFESP), Dom Cabral Foundation, Getúlio Vargas Foundation, FIA, FIPE and MONTVERO. He has authored or co-authored 9 books and he is the founder and former editor-in-chief of the International Journal of Multivariate Data Analysis. He is member and founder of the Latin American Academy of Data Science. He is a consultant to companies operating in sectors such as retail, industry, mining, banks, insurance and healthcare, with the use of Data Analysis, Machine and Deep Learning, Big Data and AI platforms, such as R, Python, SAS, Stata and IBM SPSS. Dr. Fávero is a Full Professor at the Economics, Business Administration and Accounting College and at the Polytechnic School of the University of Sao Paulo (FEAUSP and EPUSP), where he teaches Data Science, Data Analysis, Multivariate Modeling, Machine and Deep Learning and Operational Research to undergraduate, Master’s and Doctorate students. He has a Post-Doctorate degree in Data Analysis and Econometrics from Columbia University in New York. He is a tenured Professor by FEA/USP (with greater focus on Quantitative Modeling). He has a degree in Engineering from USP Polytechnic School, a post-graduate degree in Business Administration from Getúlio Vargas Foundation (FGV/SP), and he has received the titles of Master and PhD in Data Science and Quantitative Methods applied to Organizational Economics from FEA/USP. He is a Visiting Professor at the Federal University of Sao Paulo (UNIFESP), Dom Cabral Foundation, Getúlio Vargas Foundation, FIA, FIPE and MONTVERO. He has authored or co-authored 9 books and he is the founder and former editor-in-chief of the International Journal of Multivariate Data Analysis. He is member and founder of the Latin American Academy of Data Science. He is a consultant to companies operating in sectors such as retail, industry, mining, banks, insurance and healthcare, with the use of Data Analysis, Machine and Deep Learning, Big Data and AI platforms, such as R, Python, SAS, Stata and IBM SPSS.
Dr. Belfiore is Associate Professor at the Federal University of ABC (UFABC), where she teaches Data Science, Statistics, Operational Research, Production Planning and Control, and Programming and Algorithms Development to Engineering students. She has a master’s in electrical engineering and a PhD in production engineering from the Polytechnic School of the University of Sao Paulo (EPUSP). She has a post-doctorate degree in Operational Research and Computer Programming from Columbia University in New York. She takes part in several research and consultancy projects in the fields of modeling, optimization and programming. She has taught Operational Research, Multivariate Data Analysis and Operations Research and Logistics to undergraduate and master’s students at FEI University Center and at the Arts, Sciences and Humanities College of the University of Sao Paulo (EACH/USP). Her main research interests are in the fields of modeling, simulation, combinatorial optimization, heuristics and computer programming. She is the author/co-author of 9 books. She is a consultant to companies operating in sectors such as retail, industry, banks, insurance and healthcare, with the use of Process Simulation and Optimization, Data Analysis, and Machine and Deep Learning platforms, such as R, Python, Stata, IBM SPSS and ProModel.
Data Science for Business and Decision Making: An Introductory Text for Students and Practitioners
Author(s): Seyed Ali Fallahchay (Author)
Publisher: Arcler Press
Publication Date: November 1, 2020
Language: English
Print length: 198 pages
ISBN-10: 1774076217
ISBN-13: 9781774076217
Book Description
This book explores the principles underpinning data science. It considers the how and why of modern data science. The book goes further than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners in improving their decision making. Using real life examples, this book explores the possibilities and limitations of an information-based decision making framework.
Editorial Reviews
About the Author
Dr. Seyed Ali Fallahchay completed his PhD. in Business Management from De La Salle Araneta University, Philippines as well as his Masters in Business Administration in Philippines. He received his bachelor from Islamic Azad University, Iran and became licensed Engineer in 2010. Dr. Seyed Ali Fallahchay currently a professor in Business Administration at Raffles and Design Institute at Jakarta Indonesia. He is also a professor at University of Mansford, California, US. Prior to his current position in academe, he also teaches in different institution in the Philippines. He also became a Senior Program head in Business Administration as well as Research Director. He also became a professor in graduate programs and teaches several business subjects. And he also develops several course materials for graduate programs such as: Production and Operation Management, Quantitative Methods in Business, Methods of Research and Managerial Economics. He was also engaged in the industry and became a successful entrepreneur. He also authored the following books: The Economics of Innovation and Modern Scientific Communication.
Wow! eBook
