Using R and Rstudio for Data Management, Statistical Analysis, and Graphics (Hardcover, 2)

Data Input and Output
Input
Output
Further resources

Data Management
Structure and metadata
Derived variables and data manipulation
Merging, combining, and subsetting datasets
Date and time variables
Further resources
Examples

Statistical and Mathematical Functions
Probability distributions and random number generation
Mathematical functions
Matrix operations
Examples

Programming and Operating System Interface
Control flow, programming, and data generation
Functions
Interactions with the operating system

Common Statistical Procedures
Summary statistics
Bivariate statistics
Contingency tables
Tests for continuous variables
Analytic power and sample size calculations
Further resources
Examples

Linear Regression and ANOVA
Model fitting
Tests, contrasts, and linear functions of parameters
Model results and diagnostics
Model parameters and results
Further resources
Examples

Regression Generalizations and Modeling
Generalized linear models
Further generalizations
Robust methods
Models for correlated data
Survival analysis
Multivariate statistics and discriminant procedures
Complex survey design
Model selection and assessment
Further resources
Examples

A Graphical Compendium
Univariate plots
Univariate plots by grouping variable
Bivariate plots
Multivariate plots
Special-purpose plots
Further resources
Examples

Graphical Options and Configuration
Adding elements
Options and parameters
Saving graphs

Simulation
Generating data
Simulation applications
Further resources

Special Topics
Processing by group
Simulation-based power calculations
Reproducible analysis and output
Advanced statistical methods
Further resources

Case Studies
Data management and related tasks
Read variable format files
Plotting maps
Data scraping
Text mining
Interactive visualization
Manipulating bigger datasets
Constrained optimization: the knapsack problem