The Resource Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics, by Eric Goh Ming Hui, (electronic resource)

Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics, by Eric Goh Ming Hui, (electronic resource)

Label
Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics
Title
Learn R for Applied Statistics
Title remainder
With Data Visualizations, Regressions, and Statistics
Statement of responsibility
by Eric Goh Ming Hui
Creator
Contributor
Author
Author
Provider
Subject
Language
eng
Summary
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
http://library.link/vocab/creatorName
Hui, Eric Goh Ming
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
N4tXpqwVhQc
Image bit depth
0
LC call number
  • QA76.7-76.73
  • QA76.76.C65
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
SpringerLink
http://library.link/vocab/subjectName
  • Computer science
  • Big data
  • Open source software
  • Computer programming
  • Programming Languages, Compilers, Interpreters
  • Big Data
  • Probability and Statistics in Computer Science
  • Open Source
Label
Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics, by Eric Goh Ming Hui, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Chapter 1: Introduction -- Chapter 2: Getting Started -- Chapter 3: Basic -- Chapter 4: Descriptive Statistics -- Chapter 5: Data Visualizations -- Chapter 6: Inferential Statistics and Regressions
Dimensions
unknown
Extent
XV, 243 p. 111 illus.
File format
multiple file formats
Form of item
electronic
Isbn
9781484242001
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-1-4842-4200-1
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-1-4842-4200-1
Label
Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics, by Eric Goh Ming Hui, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Chapter 1: Introduction -- Chapter 2: Getting Started -- Chapter 3: Basic -- Chapter 4: Descriptive Statistics -- Chapter 5: Data Visualizations -- Chapter 6: Inferential Statistics and Regressions
Dimensions
unknown
Extent
XV, 243 p. 111 illus.
File format
multiple file formats
Form of item
electronic
Isbn
9781484242001
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-1-4842-4200-1
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-1-4842-4200-1

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