語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Learn R for Applied Statistics = Wit...
~
SpringerLink (Online service)
Learn R for Applied Statistics = With Data Visualizations, Regressions, and Statistics /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Learn R for Applied Statistics/ by Eric Goh Ming Hui.
其他題名:
With Data Visualizations, Regressions, and Statistics /
作者:
Hui, Eric Goh Ming.
面頁冊數:
XV, 243 p. 111 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Programming languages (Electronic computers). -
電子資源:
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 Statistics
With Data Visualizations, Regressions, and Statistics /[electronic resource] :by Eric Goh Ming Hui. - 1st ed. 2019. - XV, 243 p. 111 illus.online resource.
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:
1127615
Programming languages (Electronic computers).
LC Class. No.: QA76.7-76.73
Dewey Class. No.: 005.13
Learn R for Applied Statistics = With Data Visualizations, Regressions, and Statistics /
LDR
:02877nam a22004215i 4500
001
1014405
003
DE-He213
005
20200705210116.0
007
cr nn 008mamaa
008
210106s2019 xxu| s |||| 0|eng d
020
$a
9781484242001
$9
978-1-4842-4200-1
024
7
$a
10.1007/978-1-4842-4200-1
$2
doi
035
$a
978-1-4842-4200-1
050
4
$a
QA76.7-76.73
050
4
$a
QA76.76.C65
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
005.13
$2
23
100
1
$a
Hui, Eric Goh Ming.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1308623
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.
250
$a
1st ed. 2019.
264
1
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2019.
300
$a
XV, 243 p. 111 illus.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
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
Programming languages (Electronic computers).
$3
1127615
650
0
$a
Big data.
$3
981821
650
0
$a
Mathematical statistics.
$3
527941
650
0
$a
Open source software.
$3
561177
650
0
$a
Computer programming.
$3
527822
650
1 4
$a
Programming Languages, Compilers, Interpreters.
$3
669782
650
2 4
$a
Big Data.
$3
1017136
650
2 4
$a
Probability and Statistics in Computer Science.
$3
669886
650
2 4
$a
Open Source.
$3
1113081
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9781484241998
776
0 8
$i
Printed edition:
$z
9781484242018
776
0 8
$i
Printed edition:
$z
9781484246344
856
4 0
$u
https://doi.org/10.1007/978-1-4842-4200-1
912
$a
ZDB-2-CWD
912
$a
ZDB-2-SXPC
950
$a
Professional and Applied Computing (SpringerNature-12059)
950
$a
Professional and Applied Computing (R0) (SpringerNature-43716)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入