Gardener M. Beginning R: The Statistical Programming Language

Wrox – 2012, 504 pages
ISBN: 111816430X, 9781118164303Conquer 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.Introducing R: What It Is and How to Get It
Getting the Hang of R
The R Website
Downloading and Installing R from CRAN
Installing R on Your Windows Computer
Installing R on Your Macintosh Computer
Installing R on Your Linux Computer
Running the R Program
Finding Your Way with R
Getting Help via the CRAN Website and the Internet
The Help Command in R
Help for Windows Users
Help for Macintosh Users
Help for Linux Users
Help For All Users
Anatomy of a Help Item in R
Command Packages
Standard Command Packages
What Extra Packages Can Do for You
How to Get Extra Packages of R Commands
How to Install Extra Packages for Windows Users
How to Install Extra Packages for Macintosh Users
How to Install Extra Packages for Linux Users
Running and Manipulating Packages
Loading Packages
Windows-Specific Package Commands
Macintosh-Specific Package Commands
Removing or Unloading PackagesStarting Out: Becoming Familiar with R
Some Simple Math
Use R Like a Calculator
Storing the Results of Calculations
Reading and Getting Data into R
Using the combine Command for Making Data
Entering Numerical Items as Data
Entering Text Items as Data
Using the scan Command for Making Data
Entering Text as Data
Using the Clipboard to Make Data
Reading a File of Data from a Disk
Reading Bigger Data Files
The read.csv() Command
Alternative Commands for Reading Data in R
Missing Values in Data Files
Viewing Named Objects
Viewing Previously Loaded Named-Objects
Viewing All Objects
Viewing Only Matching Names
Removing Objects from R
Types of Data Items
Number Data
Text Items
Converting Between Number and Text Data
The Structure of Data Items
Vector Items
Data Frames
Matrix Objects
List Objects
Examining Data Structure
Working with History Commands
Using History Files
Viewing the Previous Command History
Saving and Recalling Lists of Commands
Alternative History Commands in Macintosh OS
Editing History Files
Saving Your Work in R
Saving the Workspace on Exit
Saving Data Files to Disk
Save Named Objects
Save Everything
Reading Data Files from Disk
Saving Data to Disk as Text Files
Writing Vector Objects to Disk
Writing Matrix and Data Frame Objects to Disk
Writing List Objects to Disk
Converting List Objects to Data FramesStarting Out: Working With Objects
Manipulating Objects
Manipulating Vectors
Selecting and Displaying Parts of a Vector
Sorting and Rearranging a Vector
Returning Logical Values from a Vector
Manipulating Matrix and Data Frames
Selecting and Displaying Parts of a Matrix or Data Frame
Sorting and Rearranging a Matrix or Data Frame
Manipulating Lists
Viewing Objects within Objects
Looking Inside Complicated Data Objects
Opening Complicated Data Objects
Quick Looks at Complicated Data Objects
Viewing and Setting Names
Rotating Data Tables
Constructing Data Objects
Making Lists
Making Data Frames
Making Matrix Objects
Re-ordering Data Frames and Matrix Objects
Forms of Data Objects: Testing and Converting
Testing to See What Type of Object You Have
Converting from One Object Form to Another
Convert a Matrix to a Data Frame
Convert a Data Frame into a Matrix
Convert a Data Frame into a List
Convert a Matrix into a List
Convert a List to Something ElseData: Descriptive Statistics and Tabulation
Summary Commands
Summarizing Samples
Summary Statistics for Vectors
Summary Commands With Single Value Results
Summary Commands With Multiple Results
Cumulative Statistics
Simple Cumulative Commands
Complex Cumulative Commands
Summary Statistics for Data Frames
Generic Summary Commands for Data Frames
Special Row and Column Summary Commands
The apply() Command for Summaries on Rows or Columns
Summary Statistics for Matrix Objects
Summary Statistics for Lists
Summary Tables
Making Contingency Tables
Creating Contingency Tables from Vectors
Creating Contingency Tables from Complicated Data
Creating Custom Contingency Tables
Creating Contingency Tables from Matrix Objects
Selecting Parts of a Table Object
Converting an Object into a Table
Testing for Table Objects
Complex (Flat) Tables
Making Flat Contingency Tables
Making Selective Flat Contingency Tables
Testing Flat Table Objects
Summary Commands for Tables
Cross Tabulation
Testing Cross-Table (xtabs) Objects
A Better Class Test
Recreating Original Data from a Contingency Table
Switching ClassData: Distribution
Looking at the Distribution of Data
Stem and Leaf Plot
Histograms
Density Function
Using the Density Function to Draw a Graph
Adding Density Lines to Existing Graphs
Types of Data Distribution
The Normal Distribution
Other Distributions
Random Number Generation and Control
Random Numbers and Sampling
The Shapiro-Wilk Test for Normality
The Kolmogorov-Smirnov Test
Quantile-Quantile Plots
A Basic Normal Quantile-Quantile Plot
Adding a Straight Line to a QQ Plot
Plotting the Distribution of One Sample Against AnotherSimple Hypothesis Testing
Using the Student’s t-test
Two-Sample t-Test with Unequal Variance
Two-Sample t-Test with Equal Variance
One-Sample t-Testing
Using Directional Hypotheses
Formula Syntax and Subsetting Samples in the t-Test
The Wilcoxon U-Test (Mann-Whitney)
Two-Sample U-Test
One-Sample U-Test
Using Directional Hypotheses
Formula Syntax and Subsetting Samples in the U-test
Paired t- and U-Tests
Correlation and Covariance
Simple Correlation
Covariance
Significance Testing in Correlation Tests
Formula Syntax
Tests for Association
Multiple Categories: Chi-Squared Tests
Monte Carlo Simulation
Yates’ Correction for n Tables
Single Category: Goodness of Fit TestsIntroduction to Graphical Analysis
Box-whisker Plots
Basic Boxplots
Customizing Boxplots
Horizontal Boxplots
Scatter Plots
Basic Scatter Plots
Adding Axis Labels
Plotting Symbols
Setting Axis Limits
Using Formula Syntax
Adding Lines of Best-Fit to Scatter Plots
Pairs Plots (Multiple Correlation Plots)
Line Charts
Line Charts Using Numeric Data
Line Charts Using Categorical Data
Pie Charts
Cleveland Dot Charts
Bar Charts
Single-Category Bar Charts
Multiple Category Bar Charts
Stacked Bar Charts
Grouped Bar Charts
Horizontal Bars
Bar Charts from Summary Data
Copy Graphics to Other Applications
Use Copy/Paste to Copy Graphs
Save a Graphic to Disk
Windows
Macintosh
LinuxFormula Notation and Complex Statistics
Examples of Using Formula Syntax for Basic Tests
Formula Notation in Graphics
Analysis of Variance (ANOVA)
One-Way ANOVA
Stacking the Data before Running Analysis of Variance
Running aov() Commands
Simple Post-hoc Testing
Extracting Means from aov() Models
Two-Way ANOVA
More about Post-hoc Testing
Graphical Summary of ANOVA
Graphical Summary of Post-hoc Testing
Extracting Means and Summary Statistics
Model Tables
Table Commands
Interaction Plots
More Complex ANOVA Models
Other Options for aov()
Replications and BalanceManipulating Data and Extracting Components
Creating Data for Complex Analysis
Data Frames
Matrix Objects
Creating and Setting Factor Data
Making Replicate Treatment Factors
Adding Rows or Columns
Summarizing Data
Simple Column and Row Summaries
Complex Summary Functions
The rowsum() Command
The apply() Command
Using tapply() to Summarize Using a Grouping Variable
The aggregate() CommandRegression (Li near Modeling)
Simple Linear Regression
Linear Model Results Objects
Coefficients
Fitted Values
Residuals
Formula
Best-Fit Line
Similarity between lm() and aov()
Multiple Regression
Formulae and Linear Models
Model Building
Adding Terms with Forward Stepwise Regression
Removing Terms with Backwards Deletion
Comparing Models
Curvilinear Regression
Logarithmic Regression
Polynomial Regression
Plotting Linear Models and Curve Fitting
Best-Fit Lines
Adding Line of Best-Fit with abline()
Calculating Lines with fitted()
Producing Smooth Curves using spline()
Confidence Intervals on Fitted Lines
Summarizing Regression Models
Diagnostic Plots
Summary of FitMore About Graphs
Adding Elements to Existing Plots
Error Bars
Using the segments() Command for Error Bars
Using the arrows() Command to Add Error Bars
Adding Legends to Graphs
Color Palettes
Placing a Legend on an Existing Plot
Adding Text to Graphs
Making Superscript and Subscript Axis Titles
Orienting the Axis Labels
Making Extra Space in the Margin for Labels
Setting Text and Label Sizes
Adding Text to the Plot Area
Adding Text in the Plot Margins
Creating Mathematical Expressions
Adding Points to an Existing Graph
Adding Various Sorts of Lines to Graphs
Adding Straight Lines as Gridlines or Best-Fit Lines
Making Curved Lines to Add to Graphs
Plotting Mathematical Expressions
Adding Short Segments of Lines to an Existing Plot
Adding Arrows to an Existing Graph
Matrix Plots (Multiple Series on One Graph)
Multiple Plots in One Window
Splitting the Plot Window into Equal Sections
Splitting the Plot Window into Unequal Sections
Exporting Graphs
Using Copy and Paste to Move a Graph
Saving a Graph to a File
Windows
Macintosh
Linux
Using the Device Driver to Save a Graph to Disk
PNG Device Driver
PDF Device Driver
Copying a Graph from Screen to Disk File
Making a New Graph Directly to a Disk FileWriting Your Own Scripts: Beginning to Program
Copy and Paste Scripts
Make Your Own Help File as Plaintext
Using Annotations with the # Character
Creating Simple Functions
One-Line Functions
Using Default Values in Functions
Simple Customized Functions with Multiple Lines
Storing Customized Functions
Making Source Code
Displaying the Results of Customized Functions and Scripts
Displaying Messages as Part of Script Output
Simple Screen Text
Display a Message and Wait for User InterventionAppendix: Answers to Exerci ses