Exploratory and Robust Data Analysis: A Modern Applied Statistics Guide Using SPSS and R
暫譯: 探索性與穩健數據分析：使用 SPSS 和 R 的現代應用統計指南
Abdel-Salam, Abdel-Salam G., Birch, Jeffrey B.
商品描述
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.
商品描述(中文翻譯)
《探索性與穩健性資料分析：使用 SPSS 和 R 的現代應用統計指南》是一本對於學生、研究人員和專業人士而言，尋求全面且實用的現代統計分析方法的重要資源。本書將傳統統計方法與當代技術相結合，強調探索性和穩健性資料分析，同時整合強大的計算工具，如 R 和 SPSS。
本書設計為中級課程和研究應用，首先介紹探索性資料分析、圖形方法和確認性統計程序的基本概念。接著介紹穩健統計方法，包括 M-估計量、高破壞估計量、自助法技術和蒙地卡羅模擬，為讀者提供處理複雜和現實世界資料情境的工具。主要主題包括迴歸分析、多重線性模型、非參數迴歸和廣義線性模型，確保在各學科中的廣泛適用性。
本書的特色在於其對理論基礎和實務應用的重視。附註的電腦課程引導讀者進行統計分析，使他們能夠有效應用技術，同時理解其理論基礎。本書通過結合經典統計程序與現代計算方法，培養分析思維，鼓勵批判性思考和數據驅動的決策。
本書提供真實世界的數據集、實用練習和詳細的軟體整合，是希望在統計嚴謹性和計算效率至關重要的時代中掌握資料分析的讀者不可或缺的指南。
作者簡介
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.
作者簡介(中文翻譯)
Abdel-Salam G. Abdel-Salam 是卡塔爾大學的統計學副教授，並且是特許統計師 (CStat) 和認證統計師 (PStat)。他擁有開羅大學的學士和碩士學位，以及維吉尼亞理工大學的碩士和博士學位，並且還擁有卡塔爾大學的工商管理碩士 (MBA)。他曾在開羅大學、維吉尼亞理工大學和奧克拉荷馬州立大學任教，並曾擔任摩根大通 (JPMorgan Chase & Co.) 風險管理的助理副總裁 (AVP)。他的專長包括統計建模、品質控制和人工智慧應用，並擁有多篇出版物和獎項，包括卡塔爾大學的傑出教學服務獎。
Jeffrey B. Birch 是一位傑出的統計學家，於1978年在華盛頓大學獲得生物統計學博士學位，自1999年以來一直擔任維吉尼亞理工大學的教授。他曾於2001年至2016年間負責統計學研究生課程，專長於穩健回歸、非參數統計和應用數據分析。他獲得多項教學獎項，並且是美國統計協會 (ASA) 和西格瑪西 (Sigma Xi) 的活躍成員。
