R for Everyone: Advanced Analytics and Graphics, 2/e (Paperback)

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, Second Edition, 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, manipulation, and visualization; 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. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny.

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.

Coverage includes

• Explore R, RStudio, and R packages
• Use R for math: variable types, vectors, calling functions, and more
• Exploit data structures, including data.frames, matrices, and lists
• Read many different types of data
• Create attractive, intuitive statistical graphics
• Write user-defined functions
• Control program flow with if, ifelse, and complex checks
• Improve program efficiency with group manipulations
• Combine and reshape multiple datasets
• Manipulate strings using R’s facilities and regular expressions
• Create normal, binomial, and Poisson probability distributions
• Build linear, generalized linear, and nonlinear models
• Program basic statistics: mean, standard deviation, and t-tests
• Train machine learning models
• Assess the quality of models and variable selection
• Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods
• Analyze univariate and multivariate time series data
• Group data via K-means and hierarchical clustering
• Prepare reports, slideshows, and web pages with knitr
• Display interactive data with RMarkdown and htmlwidgets
• Implement dashboards with Shiny
• Build reusable R packages with devtools and Rcpp

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《給程式設計師、科學家、量化交易員、Excel使用者和其他專業人士的統計計算》

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，非統計學家很難學習R，而且大多數R書籍假設讀者已具備過多的知識，無法提供幫助。《R for Everyone, Second Edition》是解決方案。

憑藉他在教授新用戶方面的豐富經驗，專業數據科學家Jared P. Lander為初學統計編程和建模的任何人寫了一本完美的教程。這本指南的組織方式使學習變得簡單和直觀，重點放在您需要完成80％現代數據任務的20％R功能上。

Lander的獨立章節從基礎知識開始，提供廣泛的實踐和示例代碼。您將下載並安裝R；瀏覽和使用R環境；掌握基本的程序控制、數據導入、操作和可視化；並進行幾個基本測試。然後，在此基礎上，您將構建幾個完整的模型，包括線性和非線性模型，並使用一些數據挖掘技術。最後，您將使用LaTeX、RMarkdown和Shiny使您的代碼可重現。

完成後，您不僅將知道如何編寫R程序，還將準備好解決您最關心的統計問題。

內容包括：

- 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
- 讀取多種不同類型的數據
- 創建引人入勝且直觀的統計圖形
- 編寫用戶定義函數
- 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
- 構建線性、廣義線性和非線性模型
- 編寫基本統計：平均值、標準差和t檢驗
- 訓練機器學習模型
- 評估模型的質量和變量選擇
- 避免過度擬合，使用彈性網和貝葉斯方法進行變量選擇
- 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RMarkdown和htmlwidgets顯示交互式數據
- 使用Shiny構建儀表板
- 使用devtools和Rcpp構建可重用的R套件

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