東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Learn R for applied statistics = wit...

Hui, Eric Goh Ming.

Linked to FindBook

Google Book

Amazon

博客來

Learn R for applied statistics = with data visualizations, regressions, and statistics /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Learn R for applied statistics/ by 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.
[NT 15003449]:	Chapter 1: Introduction -- Chapter 2: Getting Started -- Chapter 3: Basic -- Chapter 4: Descriptive Statistics -- Chapter 5: Data Visualizations -- Chapter 6: Inferential Statistics and Regressions.
Contained By:	Springer eBooks
Subject:	R (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-4200-1
ISBN:	9781484242001

Learn R for applied statistics = with 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

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

784593
R (Computer program language)

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

Dewey Class. No.: 519.502855362

Learn R for applied statistics = with data visualizations, regressions, and statistics /
LDR:02506nmm a2200337 a 4500 001 2178122
003 DE-He213
005 20190618133453.0
006 m d
007 cr nn 008maaau
008 191122s2019 cau s 0 eng d
020 $a 9781484242001 $q (electronic bk.)
020 $a 9781484241998 $q (paper)
024 7 $a 10.1007/978-1-4842-4200-1 $2 doi
035 $a 978-1-4842-4200-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.45.R3 $b H854 2019
072 7 $a UMX $2 bicssc
072 7 $a COM051010 $2 bisacsh
072 7 $a UMX $2 thema
072 7 $a UMC $2 thema
082 0 4 $a 519.502855362 $2 23
090 $a QA276.45.R3 $b H899 2019
100 1 $a Hui, Eric Goh Ming. $3 3381976
245 1 0 $a Learn R for applied statistics $h [electronic resource] : $b with data visualizations, regressions, and statistics / $c by Eric Goh Ming Hui.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2019.
300 $a xv, 243 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Introduction -- Chapter 2: Getting Started -- Chapter 3: Basic -- Chapter 4: Descriptive Statistics -- Chapter 5: Data Visualizations -- Chapter 6: Inferential Statistics and Regressions.
520 $a 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.
650 0 $a R (Computer program language) $3 784593
650 0 $a Machine learning. $3 533906
650 1 4 $a Programming Languages, Compilers, Interpreters. $3 891123
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Probability and Statistics in Computer Science. $3 891072
650 2 4 $a Open Source. $3 2210577
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-1-4842-4200-1
950 $a Professional and Applied Computing (Springer-12059)