R Programming Tutorial

Welcome to the R Programming Tutorial! If you're new to R or looking to improve your skills, this guide will help you get started.

Quick Start Guide

1. Install R and RStudio

   • Download and install R from CRAN.
   • Install RStudio for an IDE that makes coding easier.

2. Basic Syntax

   • Use > to print results.
   • Use <- to assign values.

3. Data Structures

   • Vectors: Single values, e.g., x <- 5
   • Lists: Collections of objects, e.g., y <- list("apple", 2, 3.14)

4. Control Structures

   • if statements for conditional execution.
   • Loops like for and while.

Common Use Cases

• Data Analysis

  • R is great for data analysis and statistical modeling.
  • Use packages like dplyr and ggplot2 for data manipulation and visualization.

• Machine Learning

  • R has a wide range of machine learning packages, including caret, randomForest, and xgboost.

• Graphics and Visualization

  • R provides extensive graphics capabilities with the ggplot2 package.

Resources

• R Programming for Data Science
• Advanced R Programming

For more information and tutorials, visit our R Programming Resources.