Using R and Rstudio for Data Management, Statistical Analysis, and Graphics
暫譯: 使用 R 和 RStudio 進行資料管理、統計分析與圖形繪製
Horton, Nicholas J., Kleinman, Ken
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商品描述
Improve Your Analytical Skills
Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
New to the Second Edition
- The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
- New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
- New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
- New chapter on simulation that includes examples of data generated from complex models and distributions
- A detailed discussion of the philosophy and use of the knitr and markdown packages for R
- New packages that extend the functionality of R and facilitate sophisticated analyses
- Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots
Easily Find Your Desired Task
Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.
商品描述(中文翻譯)
提升您的分析技能
本書《使用 R 和 RStudio 進行數據管理、統計分析和圖形繪製(第二版)》整合了最新的 R 套件以及新的案例研究和應用,涵蓋了統計分析師最常使用的 R 的各個方面。R 的新用戶會發現本書的簡單方法易於理解,而更高級的用戶則會欣賞這本書提供的寶貴任務導向資訊。
第二版的新內容
- 使用 RStudio,這提高了 R 用戶的生產力,並幫助用戶避免容易出錯的複製和粘貼工作流程
- 新增案例研究章節,說明有用的數據管理任務的範例,包括讀取複雜文件、製作和註解地圖、從網路“抓取”數據、挖掘文本文件以及生成動態圖形
- 新增專題章節,描述關鍵特徵,如按組處理,並探討統計學的重要領域,包括貝葉斯方法、傾向分數和自助法
- 新增模擬章節,包括從複雜模型和分佈生成的數據範例
- 詳細討論 knitr 和 markdown 套件的哲學及其在 R 中的使用
- 新增擴展 R 功能並促進複雜分析的新套件
- 重新組織和增強數據輸入和輸出、數據管理、統計和數學函數、編程、高級圖形繪製以及圖形自定義的章節
輕鬆找到您所需的任務
本版以簡短、清晰的描述條目方便地組織,繼續向用戶展示如何輕鬆在 R 中執行分析任務。用戶可以通過廣泛的索引、交叉引用和文本中的範例快速找到並實施所需的材料。數據集和代碼可在補充網站上下載。
作者簡介
Nicholas J. Horton is a professor of statistics at Amherst College. His research interests include longitudinal regression models and missing data methods, with applications in psychiatric epidemiology and substance abuse research.
Ken Kleinman is an associate professor in the Department of Population Medicine at Harvard Medical School. His research deals with clustered data analysis, surveillance, and epidemiological applications in projects ranging from vaccine and bioterrorism surveillance to observational epidemiology to individual-, practice-, and community-randomized interventions.
作者簡介(中文翻譯)
Nicholas J. Horton 是阿默斯特學院的統計學教授。他的研究興趣包括縱向迴歸模型和缺失數據方法,應用於精神病流行病學和物質濫用研究。
Ken Kleinman 是哈佛醫學院人口醫學系的副教授。他的研究涉及聚類數據分析、監測以及流行病學應用,涵蓋從疫苗和生物恐怖主義監測到觀察性流行病學,再到個體、實踐和社區隨機干預的各種項目。