UID:
almahu_9948104409902882
Format:
XV, 243 p. 111 illus.
,
online resource.
ISBN:
9781484242001
Content:
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. You will: 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.
Note:
Chapter 1: Introduction -- Chapter 2: Getting Started -- Chapter 3: Basic -- Chapter 4: Descriptive Statistics -- Chapter 5: Data Visualizations -- Chapter 6: Inferential Statistics and Regressions.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9781484241998
Additional Edition:
Printed edition: ISBN 9781484242018
Additional Edition:
Printed edition: ISBN 9781484246344
Language:
English
Subjects:
Computer Science
DOI:
10.1007/978-1-4842-4200-1
URL:
https://doi.org/10.1007/978-1-4842-4200-1
URL:
Volltext
(URL des Erstveröffentlichers)
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