Introduction and Overview of R Language
Introduction to R
  • R as a language
  • Working with data in R
The R ecosystem
  • Why use R?
  • Getting started
  • Installation and setup
  • Packages
Data types
  • Character
  • Factor
  • Integer
  • Float
  • Date and time
Data structures
  • Vectors
  • Matrices
  • Lists
  • Data frames
Data handling
  • Importing data from multiple sources/formats like .csv, .txt, .xlsx, SAS and SPSS files
  • Exporting data to multiple formats
  • Handling data frames: filtering, sorting, merging
  • PLYR package for easy data manipulation
Functions
  • Commonly used built in functions
  • Writing user defined functions
  • Installing packages
  • Looping functions
  • The "apply" family of functions
  • Basic visualization
Basic statistics in R
  • Distributions
  • Testing
  • Modeling
Graphics in R
  • Graphics for exploratory data analysis
  • Standard graphic displays
The R environment
  • R in the cloud
Statistical analysis with R
  • Linear models
  • Generalized linear models
Advanced statistical modeling with R
  • Density estimation
  • Survival analysis
  • Classification
  • Clustering
Introduction to Writing R Packages Integrating with other tools.
  • Tableau
  • Python
  • CPP