R for Everyone: Advanced Analytics and Graphics (Paperback)

Jared P. Lander



Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals

Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution.

Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks.

Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques.

By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most.



• Exploring R, RStudio, and R packages

• Using R for math: variable types, vectors, calling functions, and more

• Exploiting data structures, including data.frames, matrices, and lists

• Creating attractive, intuitive statistical graphics

• Writing user-defined functions

• Controlling program flow with if, ifelse, and complex checks

• Improving program efficiency with group manipulations

• Combining and reshaping multiple datasets

• Manipulating strings using R’s facilities and regular expressions

• Creating normal, binomial, and Poisson probability distributions

• Programming basic statistics: mean, standard deviation, and t-tests

• Building linear, generalized linear, and nonlinear models

• Assessing the quality of models and variable selection

• Preventing overfitting, using the Elastic Net and Bayesian methods

• Analyzing univariate and multivariate time series data

• Grouping data via K-means and hierarchical clustering

• Preparing reports, slideshows, and web pages with knitr

• Building reusable R packages with devtools and Rcpp

• Getting involved with the R global community




使用開源語言R,您可以建立強大的統計模型來回答您最具挑戰性的問題。傳統上,非統計學家學習R一直很困難,大多數R書籍假設讀者已具備過多的知識,無法提供幫助。《R for Everyone》是解決方案。

憑藉其豐富的教學經驗,專業數據科學家Jared P. Lander為初學統計編程和建模的人撰寫了完美的教程。這本指南的組織方式使學習變得輕鬆和直觀,重點放在您需要完成80%現代數據任務的20%R功能上。




• 探索R、RStudio和R套件
• 使用R進行數學運算:變量類型、向量、調用函數等
• 利用數據結構,包括data.frames、矩陣和列表
• 創建引人入勝、直觀的統計圖形
• 編寫用戶自定義函數
• 使用if、ifelse和複雜檢查控制程序流程
• 通過群組操作提高程序效率
• 結合和重塑多個數據集
• 使用R的功能和正則表達式操作字符串
• 創建正態、二項和泊松概率分佈
• 編寫基本統計:平均值、標準差和t檢驗
• 構建線性、廣義線性和非線性模型
• 評估模型的質量和變量選擇
• 避免過度擬合,使用Elastic Net和貝葉斯方法
• 分析單變量和多變量時間序列數據
• 通過K-means和階層聚類對數據進行分組
• 使用knitr準備報告、簡報和網頁
• 使用devtools和Rcpp構建可重用的R套件
• 參與R全球社區