Exploratory and Robust Data Analysis: A Modern Applied Statistics Guide Using SPSS and Python

Abdel-Salam, Abdel-Salam G.; Birch, Jeffrey B.

ISBN 10: 1032931922 / ISBN 13: 9781032931920

Published by Chapman and Hall/CRC, 2025

About this Item

Seller Inventory # 18403871133

Bibliographic Details

• Title: Exploratory and Robust Data Analysis: A Modern Applied Statistics Guide Using SPSS and Python
• Publisher: Chapman and Hall/CRC
• Publication Date: 2025
• Language: English
• ISBN 10: 1032931922
• ISBN 13: 9781032931920
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Exploratory and Robust Data Analysis: A Modern Applied Statistics Guide Using SPSS and R is an essential resource for students, researchers, and professionals seeking a comprehensive yet practical approach to modern statistical analysis. This book bridges traditional statistical methods with contemporary techniques, emphasizing exploratory and robust data analysis while integrating powerful computational tools such as R and SPSS.

Designed for intermediate-level courses and research applications, the book begins with fundamental concepts in exploratory data analysis, graphical methods, and confirmatory statistical procedures. It then introduces robust statistical methods, including M-estimators, high breakdown estimators, bootstrap techniques, and Monte Carlo simulations, equipping readers with tools to handle complex and real-world data scenarios. Key topics include regression analysis, multiple linear models, nonparametric regression, and generalized linear models, ensuring broad applicability across disciplines.

What sets this book apart is its emphasis on theoretical foundations and hands-on applications. Annotated computer sessions guide readers through statistical analysis, enabling them to apply techniques effectively while understanding their theoretical underpinnings. This book fosters an analytical mindset that encourages critical thinking and data-driven decision-making by combining classical statistical procedures with modern computational methods.

With real-world datasets, practical exercises, and detailed software integration, this book is an indispensable guide for those looking to master data analysis in an era where statistical rigor and computational efficiency are paramount.

About the Author

Abdel-Salam G. Abdel-Salam is an associate professor of statistics at Qatar University and a chartered (CStat) and certified (PStat) statistician. He holds degrees from Cairo University (BS, MS) and Virginia Tech (MS, PhD) and also holds an MBA from Qatar University. He has taught at Cairo University, Virginia Tech, and Oklahoma State University and was Assistant Vice President (AVP) in risk management at JPMorgan Chase & Co. His expertise includes statistical modeling, quality control, and AI applications, with numerous publications and awards, including Qatar University’s Outstanding Faculty Service Award.

Jeffrey B. Birch, a distinguished statistician, earned his PhD in biostatistics from the University of Washington (1978) and has been a professor at Virginia Tech since 1999. He directed graduate programs in statistics (2001–2016) and specializes in robust regression, nonparametric statistics, and applied data analysis. A recipient of multiple teaching awards, he is an active ASA and Sigma Xi member.