Learn R for Applied Statistics: With Data Visualizations, Regressions, and Statistics (應用統計學的R語言學習:數據視覺化、迴歸分析與統計方法)
Eric Goh Ming Hui
- 出版商: Apress
- 出版日期: 2018-12-01
- 售價: $2,170
- 貴賓價: 9.5 折 $2,062
- 語言: 英文
- 頁數: 243
- 裝訂: Paperback
- ISBN: 1484241991
- ISBN-13: 9781484241998
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相關分類:
R 語言、機率統計學 Probability-and-statistics、Data-visualization
海外代購書籍(需單獨結帳)
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相關主題
商品描述
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions.
Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations.
What You Will Learn
- Discover R, statistics, data science, data mining, and big data
- Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions
- Work with descriptive statistics
- Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots
- Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions
Who This Book Is For
Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.
商品描述(中文翻譯)
學習應用統計學的 R 程式語言基礎,以進行資料科學和資料挖掘中的資料探索和分析。本書涵蓋的主題包括從 R 語法基礎、描述性統計和資料視覺化到推論統計和回歸分析。在學習了 R 的語法後,您將進行資料視覺化,如直方圖和箱形圖,描述性統計以及推論統計,如 t 檢驗、卡方檢驗、ANOVA、非參數檢驗和線性回歸。
《學習應用統計學的 R》是一本及時的技能遷移書,它為您提供了 R 程式設計的基礎知識,並介紹了應用統計學進行資料探索的方法。
您將學到什麼
- 了解 R、統計學、資料科學、資料挖掘和大數據
- 掌握 R 程式設計的基礎知識,包括變數和算術、向量、列表、資料框、條件語句、迴圈和函數
- 使用描述性統計
- 創建資料視覺化,包括長條圖、折線圖、散點圖、箱形圖、直方圖和散點圖
- 使用推論統計,包括 t 檢驗、卡方檢驗、ANOVA、非參數檢驗、線性回歸和多元線性回歸
適合閱讀對象
對資料科學特別是應用統計學進行資料探索以及使用 R 程式設計進行資料視覺化感興趣的人。