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Learn R for applied statisticswith d...

Hui, Eric Goh Ming.

Learn R for applied statisticswith data visualizations, regressions, and statistics /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Learn R for applied statisticsby Eric Goh Ming Hui.
Reminder of title:	with data visualizations, regressions, and statistics /
Author:	Hui, Eric Goh Ming.
Published:	Berkeley, CA :Apress :2019.
Description:	xv, 243 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	R (Computer program language)
Online resource:	https://doi.org/10.1007/978-1-4842-4200-1
ISBN:	9781484242001$q(electronic bk.)

Learn R for applied statisticswith data visualizations, regressions, and statistics /
Hui, Eric Goh Ming.

Learn R for applied statisticswith data visualizations, regressions, and statistics /[electronic resource] :by Eric Goh Ming Hui. - Berkeley, CA :Apress :2019. - xv, 243 p. :ill., digital ;24 cm.

Chapter 1: Introduction -- Chapter 2: Getting Started -- Chapter 3: Basic -- Chapter 4: Descriptive Statistics -- Chapter 5: Data Visualizations -- Chapter 6: Inferential Statistics and Regressions.

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.

ISBN: 9781484242001$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-4200-1doiSubjects--Topical Terms:

210846
R (Computer program language)

LC Class. No.: QA276.45.R3 / H854 2019

Dewey Class. No.: 519.502855362

Learn R for applied statisticswith data visualizations, regressions, and statistics /
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