Beginning R : an introduction to statistical programming /: an introduction to statistical programming. ([2015])
- Record Type:
- Book
- Title:
- Beginning R : an introduction to statistical programming /: an introduction to statistical programming. ([2015])
- Main Title:
- Beginning R : an introduction to statistical programming
- Further Information:
- Note: Joshua F. Wiley, Larry A. Pace.
- Authors:
- Wiley, Joshua F
Pace, Larry A - Contents:
- At a Glance; Contents; About the Author; In Memoriam; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Getting Star ted; 1.1 What is R, Anyway?; 1.2 A First R Session; 1.3 Your Second R Session; 1.3.1 Working with Indexes; 1.3.2 Representing Missing Data in R; 1.3.3 Vectors and Vectorization in R; 1.3.4 A Brief Introduction to Matrices; 1.3.5 More on Lists; 1.3.6 A Quick Introduction to Data Frames; Chapter 2: Dealing with Dates, Strings, and Data Frames; 2.1 Working with Dates and Times; 2.2 Working with Strings. 2.3 Working with Data Frames in the Real World 2.3.1 Finding and Subsetting Data; 2.4 Manipulating Data Structures; 2.5 The Hard Work of Working with Larger Datasets; Chapter 3: Input and Output; 3.1 R Input; 3.1.1 The R Editor; 3.1.2 The R Data Editor; 3.1.3 Other Ways to Get Data Into R; 3.1.4 Reading Data from a File; 3.1.5 Getting Data from the Web; 3.2 R Output; 3.2.1 Saving Output to a File; Chapter 4: Control Structures; 4.1 Using Logic; 4.2 Flow Control; 4.2.1 Explicit Looping; 4.2.2 Implicit Looping; 4.3 If, If-Else, and ifelse() Statements. Chapter 5: Functional Programming 5.1 Scoping Rules; 5.2 Reserved Names and Syntactically Correct Names; 5.3 Functions and Arguments; 5.4 Some Example Functions; 5.4.1 Guess the Number; 5.4.2 A Function with Arguments; 5.5 Classes and Methods; 5.5.1 S3 Class and Method Example; 5.5.2 S3 Methods for Existing Classes; Chapter 6: Probability Distributions; 6.1 Discrete Probability Distributions; 6.2At a Glance; Contents; About the Author; In Memoriam; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Getting Star ted; 1.1 What is R, Anyway?; 1.2 A First R Session; 1.3 Your Second R Session; 1.3.1 Working with Indexes; 1.3.2 Representing Missing Data in R; 1.3.3 Vectors and Vectorization in R; 1.3.4 A Brief Introduction to Matrices; 1.3.5 More on Lists; 1.3.6 A Quick Introduction to Data Frames; Chapter 2: Dealing with Dates, Strings, and Data Frames; 2.1 Working with Dates and Times; 2.2 Working with Strings. 2.3 Working with Data Frames in the Real World 2.3.1 Finding and Subsetting Data; 2.4 Manipulating Data Structures; 2.5 The Hard Work of Working with Larger Datasets; Chapter 3: Input and Output; 3.1 R Input; 3.1.1 The R Editor; 3.1.2 The R Data Editor; 3.1.3 Other Ways to Get Data Into R; 3.1.4 Reading Data from a File; 3.1.5 Getting Data from the Web; 3.2 R Output; 3.2.1 Saving Output to a File; Chapter 4: Control Structures; 4.1 Using Logic; 4.2 Flow Control; 4.2.1 Explicit Looping; 4.2.2 Implicit Looping; 4.3 If, If-Else, and ifelse() Statements. Chapter 5: Functional Programming 5.1 Scoping Rules; 5.2 Reserved Names and Syntactically Correct Names; 5.3 Functions and Arguments; 5.4 Some Example Functions; 5.4.1 Guess the Number; 5.4.2 A Function with Arguments; 5.5 Classes and Methods; 5.5.1 S3 Class and Method Example; 5.5.2 S3 Methods for Existing Classes; Chapter 6: Probability Distributions; 6.1 Discrete Probability Distributions; 6.2 The Binomial Distribution; 6.2.1 The Poisson Distribution; 6.2.2 Some Other Discrete Distributions; 6.3 Continuous Probability Distributions; 6.3.1 The Normal Distribution. 6.3.2 The t Distribution 6.3.3 The F distribution; 6.3.4 The Chi-Square Distribution; References; Chapter 7: Working with Tables; 7.1 Working with One-Way Tables; 7.2 Working with Two-Way Tables; Chapter 8: Descriptive Statistics and Exploratory Data Analysis; 8.1 Central Tendency ; 8.1.1 The Mean; 8.1.2 The Median; 8.1.3 The Mode; 8.2 Variability ; 8.2.1 The Range; 8.2.2 The Variance and Standard Deviation ; 8.3 Boxplots and Stem-and-Leaf Displays ; 8.4 Using the fBasics Package for Summary Statistics; References; Chapter 9: Working with Graphics. 9.1 Creating Effective Graphics 9.2 Graphing Nominal and Ordinal Data; 9.3 Graphing Scale Data; 9.3.1 Boxplots Revisited ; 9.3.2 Histograms and Dotplots; 9.3.3 Frequency Polygons and Smoothed Density Plots; 9.3.4 Graphing Bivariate Data; References; Chapter 10: Traditional Statistical Methods; 10.1 Estimation and Confidence Intervals; 10.1.1 Confidence Intervals for Means; 10.1.2 Confidence Intervals for Proportions; 10.1.3 Confidence Intervals for the Variance; 10.2 Hypothesis Tests with One Sample; 10.3 Hypothesis Tests with Two Samples; References. … (more)
- Edition:
- Second edition
- Publisher Details:
- Berkeley, CA : Apress
- Publication Date:
- 2015
- Copyright Date:
- 2015
- Extent:
- 1 online resource
- Subjects:
- 005.13/3
Computer science
R (Computer program language)
Statistics -- Data processing
COMPUTERS -- Programming Languages -- General
R (Computer program language)
Statistics -- Data processing
Computers -- Mathematical & Statistical Software
Mathematical & statistical software
Computer software
Programming & scripting languages: general
Electronic book
Electronic books - Languages:
- English
- ISBNs:
- 9781484203736
1484203739 - Related ISBNs:
- 9781484203743
1484203747 - Notes:
- Note: Includes bibliographical references and index.
Note: Online resource; title from PDF title page (EBSCO, viewed October 29, 2015). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.374807
- Ingest File:
- 02_355.xml