WorldCat Linked Data Explorer

http://worldcat.org/entity/work/id/1118105605

Beginning R the statistical programming language : programming & software development

Chapter 3: Starting Out: Working; Manipulating Objects; Viewing Objects within Objects; Constructing Data Objects; Forms of Data Objects: Testing and Converting; Summary; Chapter 4: Data: Descriptive Statistics and Tabulation; Summary Commands; Summarizing Samples; Summary Tables; Summary; Chapter 5: Data: Distribution; Looking at the Distribution of Data; Summary; Chapter 6: Simple Hypothesis Testing; Using the Student's t-test; The Wilcoxon U-Test (Mann-Whitney); Paired t- and U-Tests; Correlation and Covariance; Tests for Association; Summary.

Open All Close All

http://schema.org/about

http://schema.org/alternateName

  • "R"
  • "R: the statistical programming lanugage"@en

http://schema.org/description

  • "Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex s."
  • "Chapter 3: Starting Out: Working; Manipulating Objects; Viewing Objects within Objects; Constructing Data Objects; Forms of Data Objects: Testing and Converting; Summary; Chapter 4: Data: Descriptive Statistics and Tabulation; Summary Commands; Summarizing Samples; Summary Tables; Summary; Chapter 5: Data: Distribution; Looking at the Distribution of Data; Summary; Chapter 6: Simple Hypothesis Testing; Using the Student's t-test; The Wilcoxon U-Test (Mann-Whitney); Paired t- and U-Tests; Correlation and Covariance; Tests for Association; Summary."@en
  • "Chapter 3: Starting Out: Working; Manipulating Objects; Viewing Objects within Objects; Constructing Data Objects; Forms of Data Objects: Testing and Converting; Summary; Chapter 4: Data: Descriptive Statistics and Tabulation; Summary Commands; Summarizing Samples; Summary Tables; Summary; Chapter 5: Data: Distribution; Looking at the Distribution of Data; Summary; Chapter 6: Simple Hypothesis Testing; Using the Student's t-test; The Wilcoxon U-Test (Mann-Whitney); Paired t- and U-Tests; Correlation and Covariance; Tests for Association; Summary"
  • "Conquer the complexities of this open source statistical languageR is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex statistics."@en
  • "Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex statistics, manipulating data and extracting components, and rudimentary programming R, the open source statistical language increasingly used to handle statistics and produces publication quality graphs, is notoriously complex. This book makes R easier to understand through the use of simple statistical examples, teaching the necessary elements in the context in which R is actually used Covers getting started with R and using it for simple summary statistics, hypothesis testing, and graphs. Shows how to use R for formula notation, complex statistics, manipulating data, extracting components, and regression. Provides beginning programming instruction for those who want to write their own scripts Beginning R offers anyone who needs to perform statistical analysis the information necessary to use R with confidence."@en

http://schema.org/genre

  • "Electronic books"
  • "Electronic books"@en
  • "Ressources Internet"

http://schema.org/name

  • "Beginning R the statistical programming language : programming & software development"
  • "Beginning R the statistical programming language : programming & software development"@en
  • "Beginning R : the statistical programming language"@en
  • "Beginning R : the statistical programming language"
  • "Beginning R the Statistical Programming Language"@en
  • "Beninning R : the statistical programming language"
  • "Beginning R the statistical programming language"