Applied Linear Regression for Business Analytics with R: A Practical Guide to Data Science with Case Studies (International Series in Operations Research & Management Science, 337, Band 337) - Hardcover

McGibney, Daniel P.

Hardcover

ISBN 10: 303121479X ISBN 13: 9783031214790

Verlag: Springer, 2023

Inhaltsangabe

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.

Über diesen Titel

Über die Autorin bzw. den Autor

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.

Von der hinteren Coverseite

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2023
• Sprache: Englisch
• ISBN 10: 303121479X
• ISBN 13: 9783031214790
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 293
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Deutschland