Overview
- Provides a variety of in-depth case studies across different business disciplines
- Offers an intuitive account of linear regression to readers also without advanced mathematical knowledge
- Engages worked-through examples accompanied by detailed coding; extra data files at www.businessregression.com
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 337)
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About this book
Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.
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Keywords
Table of contents (9 chapters)
Authors and Affiliations
About the author
Dr. Daniel McGibney is an Assistant Professor of Professional Practice at the University of Miami Herbert Business School, USA. He currently teaches analytics to both graduate and undergraduate students. Over the years, he has taught many analytics and data science classes, ranging from Basic Statistics to Big Data Analytics and Deep Learning. He has taught Applied Linear Regression Analysis to students pursuing their MSBA, MBA, MST, and MAcc. He also actively oversees and mentors graduate capstone projects in Analytics for MSBA students, collaborating with Deloitte, Visa, Carnival, Citi, Experian, and many other companies. Dr. McGibney formerly served as the program director for the Herbert Business School’s MSBA degree program. He advised students, oversaw admissions, expanded industry partnerships, and advanced the program curriculum during his tenure as program director.
Bibliographic Information
Book Title: Applied Linear Regression for Business Analytics with R
Book Subtitle: A Practical Guide to Data Science with Case Studies
Authors: Daniel P. McGibney
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-3-031-21480-6
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-21479-0Published: 03 June 2023
Softcover ISBN: 978-3-031-21482-0Due: 04 July 2023
eBook ISBN: 978-3-031-21480-6Published: 02 June 2023
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XVII, 276
Number of Illustrations: 33 b/w illustrations, 53 illustrations in colour
Topics: Operations Research/Decision Theory, Statistical Theory and Methods, IT in Business, Computer Science, general, Statistics and Computing/Statistics Programs