Learn R for Applied Statistics: With Data Visualizations, Regressions, and Statistics
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. Aft...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Berkeley, CA
Apress L.P.
2018
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781484242001/?ar |
| Zusammenfassung: | 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. |
| Beschreibung: | Wilcoxon Signed Rank Test. - Includes bibliographical references and index. - Print version record |
| Umfang: | 1 Online-Ressource (254 Seiten) |
| ISBN: | 9781484242001 1484242009 1484242017 1484246349 1484241991 9781484241998 |
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| id | ZDB-30-ORH-047609737 |
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| indexdate | 2025-01-17T11:21:17Z |
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| language | English |
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| spelling | Hui, Eric Goh Ming VerfasserIn aut Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics Berkeley, CA Apress L.P. 2018 1 Online-Ressource (254 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Wilcoxon Signed Rank Test. - Includes bibliographical references and index. - Print version record 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. R Machine learning Apprentissage automatique MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General 9781484241998 Erscheint auch als Druck-Ausgabe 9781484241998 |
| spellingShingle | Hui, Eric Goh Ming Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics R Machine learning Apprentissage automatique MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General |
| title | Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics |
| title_auth | Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics |
| title_exact_search | Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics |
| title_full | Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics |
| title_fullStr | Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics |
| title_full_unstemmed | Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics |
| title_short | Learn R for Applied Statistics |
| title_sort | learn r for applied statistics with data visualizations regressions and statistics |
| title_sub | With Data Visualizations, Regressions, and Statistics |
| topic | R Machine learning Apprentissage automatique MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General |
| topic_facet | R Machine learning Apprentissage automatique MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General |
| work_keys_str_mv | AT huiericgohming learnrforappliedstatisticswithdatavisualizationsregressionsandstatistics |