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Beginning R : an introduction to statistical programming

Author: Joshua F Wiley; Larry A Pace
Publisher: [Berkeley, CA] : Apress, [2015] ©2015
Series: Expert's voice in programming.
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based  Read more...
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Genre/Form: Electronic books
Electronic book
Additional Physical Format: Print version:
Wiley, Joshua F.
Beginning R.
[Berkeley, CA] : Apress, [2015]
(OCoLC)921191221
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Joshua F Wiley; Larry A Pace
ISBN: 9781484203736 1484203739
OCLC Number: 926914972
Notes: Includes index.
Description: 1 online resource.
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; 6.2 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.
Series Title: Expert's voice in programming.
Responsibility: Joshua F. Wiley, Larry A. Pace.

Abstract:

Beginning R, Second Edition is a hands-on book showing howto use the R language, write and save R scripts, read in data files, and writecustom statistical functions as well as use built in functions.  Read more...

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