Scientific Data Analysis with R: Biostatistical Applications

Rahman, Azizur, Abdulla, Faruq, Hossain, MD Moyazzem

  • 出版商: CRC
  • 出版日期: 2024-11-27
  • 售價: $3,880
  • 貴賓價: 9.5$3,686
  • 語言: 英文
  • 頁數: 402
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032546921
  • ISBN-13: 9781032546926
  • 相關分類: R 語言Data Science
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

In an era marked by exponential growth in data generation and an unprecedented convergence of technology and healthcare, the intersection of biostatistics and data science has become a pivotal domain. This book is the ideal companion in navigating the convergence of statistical methodologies and data science techniques with diverse applications implemented in the open-source environment of R. It is designed to be a comprehensive guide, marrying the principles of biostatistics with the practical implementation of statistics and data science in R, thereby empowering learners, researchers, and practitioners with the tools necessary to extract meaningful knowledge from biological, health, and medical datasets.

This book is intended for students, researchers, and professionals eager to harness the combined power of biostatistics, data science, and the R programming language while gathering vital statistical knowledge needed for cutting-edge scientists in all fields. It is useful for those seeking to understand the basics of data science and statistical analysis, or looking to enhance their skills in handling any simple or complex data including biological, health, medical, and industry data.

Key Features:

  • Presents contemporary concepts of data science and biostatistics with real-life data analysis examples
  • Promotes the evolution of fundamental and advanced methods applying to real-life problem-solving cases
  • Explores computational statistical data science techniques from initial conception to recent developments of biostatistics
  • Provides all R codes and real-world datasets to practice and competently apply into reader's own domains
  • Written in an exclusive state-of-the-art deductive approach without any theoretical hitches to support all contemporary readers

商品描述(中文翻譯)

在這個數據生成呈指數增長、科技與醫療前所未有融合的時代,生物統計學與數據科學的交匯已成為一個關鍵領域。本書是探索統計方法與數據科學技術融合的理想伴侶,涵蓋在開源環境R中實施的多樣應用。它旨在成為一本全面的指南,將生物統計學的原則與R中統計和數據科學的實際應用結合起來,從而賦予學習者、研究者和實踐者必要的工具,以從生物、健康和醫療數據集中提取有意義的知識。

本書適合學生、研究者和專業人士,渴望利用生物統計學、數據科學和R程式語言的綜合力量,同時獲取尖端科學家在各個領域所需的關鍵統計知識。對於那些希望了解數據科學和統計分析基礎,或希望提升處理任何簡單或複雜數據(包括生物、健康、醫療和行業數據)技能的人來說,本書都非常有用。

主要特色:
- 提供當代數據科學和生物統計學的概念,並附有實際數據分析範例
- 促進基本和進階方法的演變,應用於現實問題解決案例
- 探索計算統計數據科學技術,從初步構想到生物統計學的最新發展
- 提供所有R代碼和真實世界數據集,以便讀者練習並熟練應用於自己的領域
- 採用獨特的最先進演繹方法撰寫,沒有任何理論上的障礙,以支持所有當代讀者

作者簡介

Azizur Rahman is an associate professor at the School of Computing, Mathematics and Engineering and the 'Data Mining Research Group' leader at Charles Sturt University, Australia. He earned a BSc (Honours) in Statistical Science, an MSc (Thesis) in Biostatistics, and a PhD in Economics and Statistics from the University of Canberra under the supervision of Professor Ann Harding, AO FASSA. He worked as a biostatistical research fellow in the Faculty of Health and Medical Sciences at the University of Adelaide. Professor Rahman is a statistician and data scientist with expertise in developing and applying novel methodologies, models, and technologies. He designs projects to understand multidisciplinary research issues within various fields with the interaction or adaptation of statistics, data science, AI, and ML. Professor Rahman develops data-centric 'alternative computational methods in microsimulation modelling technologies', which are handy tools for decision-making processes in government and nongovernmental organizations, precision estimation, policy analysis, and evaluation. He founded and runs the 'Data Analytics Lab' at Charles Sturt. Professor Rahman has accrued more than $4.03 million of external research funding and over 203 scholarly publications and received several awards, including the 2023 Charles Sturt Excellence Awards and the ANZRSAI's 2023 Outstanding Service Award.

Faruq Abdulla is an outstanding graduate researcher, statistician, and data scientist, adeptly practicing in academia and industry. His expertise includes applying and developing sophisticated statistical, data science, and machine learning methodologies, models, and techniques in biological and medical sciences. With a keen focus on high-dimensional simulation and real-world data, he tackles pressing public health challenges, thereby contributing to evidence-based policy formulation. He has completed an MSc (Thesis) and a BSc (Honors) in Statistics from the Islamic University, Kushtia, Bangladesh. His academic excellence is evident through his first place in his class in order of merit at both the BSc and MSc levels, earning him the prestigious Presidential Gold Medal for achieving the highest marks in the Faculty of Applied Science & Technology in the MSc final examination. Moreover, Abdulla actively contributes to the scientific community by advancing scientific knowledge through his research findings published in renowned international peer-reviewed and high-impact journals indexed in SCOPUS and SCI. Additionally, he serves as a discerning reviewer for esteemed peer-reviewed journals published by world-class publishers.

Md. Moyazzem Hossain is an applied statistician and data scientist specializing in developing and applying contemporary statistical and data science methodologies, models, and techniques and currently holding the position of Professor in the Department of Statistics and Data Science at Jahangirnagar University, Bangladesh. Hossain earned his PhD from the School of Mathematics, Statistics, and Physics at Newcastle University, UK. He also obtained his BSc (Honors), MSc (Thesis), and MPhil from the Department of Statistics, Jahangirnagar University, Bangladesh. Hossain's outstanding contributions have been recognized through accolades such as the 'Best Conference Paper' award at the Australia and New Zealand Regional Science Association International 45th Annual Conference, held at Charles Sturt University, Wagga Wagga, Australia, on 1-2 December 2022. His research findings have been disseminated through numerous peer-reviewed publications in esteemed journals. Additionally, Hossain has served as an academic editor for PloS ONE and contributed as a reviewer for various international journals.

作者簡介(中文翻譯)

Azizur Rahman 是澳洲查爾斯特大學計算、數學與工程學院的副教授,以及「數據挖掘研究小組」的負責人。他在坎培拉大學獲得統計科學的榮譽學士學位、生物統計的碩士學位(論文)以及經濟學和統計學的博士學位,指導教授為 Ann Harding 教授(AO FASSA)。他曾在阿德萊德大學健康與醫學科學學院擔任生物統計研究員。Rahman 教授是一位統計學家和數據科學家,專長於開發和應用新穎的方法論、模型和技術。他設計項目以理解各領域內的多學科研究問題,並結合或調整統計學、數據科學、人工智慧和機器學習。Rahman 教授開發以數據為中心的「微模擬建模技術中的替代計算方法」,這些方法是政府和非政府組織在決策過程、精確估算、政策分析和評估中的實用工具。他創立並運營查爾斯特的「數據分析實驗室」。Rahman 教授已獲得超過 403 萬美元的外部研究資金,並發表了超過 203 篇學術論文,獲得多項獎項,包括 2023 年查爾斯特卓越獎和 ANZRSAI 2023 年傑出服務獎。

Faruq Abdulla 是一位傑出的研究生、統計學家和數據科學家,能夠在學術界和產業界靈活運用。他的專長包括在生物和醫學科學中應用和開發複雜的統計、數據科學和機器學習方法、模型和技術。他專注於高維模擬和真實世界數據,解決緊迫的公共衛生挑戰,從而為基於證據的政策制定做出貢獻。他在孟加拉國庫什提亞的伊斯蘭大學完成了碩士學位(論文)和榮譽學士學位,並在學士和碩士階段均以優異成績名列前茅,獲得了榮譽的總統金獎,以表彰他在碩士最終考試中取得的最高分。此外,Abdulla 積極通過在知名國際同行評審和高影響力期刊上發表的研究成果,為科學社群做出貢獻。此外,他還擔任世界級出版商發行的同行評審期刊的審稿人。

Md. Moyazzem Hossain 是一位應用統計學家和數據科學家,專注於開發和應用當代統計和數據科學方法、模型和技術,目前擔任孟加拉國賈漢基爾大學統計與數據科學系的教授。Hossain 在英國紐卡斯爾大學的數學、統計和物理學院獲得博士學位。他還在賈漢基爾大學的統計系獲得榮譽學士學位、碩士學位(論文)和哲學碩士學位。Hossain 的卓越貢獻獲得了多項榮譽,包括在 2022 年 12 月 1-2 日於查爾斯特大學舉行的澳洲和新西蘭區域科學協會第 45 屆年會上獲得的「最佳會議論文」獎。他的研究成果已通過多篇在知名期刊上發表的同行評審文章進行了廣泛傳播。此外,Hossain 還擔任 PloS ONE 的學術編輯,並為多個國際期刊擔任審稿人。