R Programming Compilation 📊

A comprehensive collection of R programming exercises, laboratory activities, and examinations for the SIA102 course, focused on building practical skills in statistical computing and data analysis.

📋 Overview

A collection of progressive R programming exercises for SIA102, covering statistical computing and data analysis. Content ranges from basic syntax to advanced data manipulation techniques, forming a structured learning path that builds skills incrementally through hands-on practice with real-world analytical challenges.

📚 Prerequisites

• Basic Programming Knowledge: Familiarity with programming concepts (variables, functions, loops)
• Statistical Fundamentals: Understanding of basic statistical concepts
• Math Background: Basic algebra and arithmetic skills
• Computer Access: System capable of running R and RStudio

🔧 Tech Stack

• Programming Language: R - Used for statistical computing and data analysis
• Development Environment: RStudio - Integrated Development Environment for R

🌟 Features

• Basic R Syntax and Operations

  • Variable assignment and arithmetic operations
  • Data types and structures
  • Built-in functions

• Control Structures

  • Conditional statements (if-else)
  • Loops (for, while, repeat)
  • Logical operators

• Vector Manipulation

  • Creation and indexing
  • Element-wise operations
  • Vector functions

• Data Processing

  • Input/output operations
  • Data categorization
  • Aggregation and summarization

• Mathematical Analysis

  • Statistical calculations
  • Advanced mathematical operations
  • Numerical computations

📁 Project Structure

The repository is organized into a series of activities, each representing progressively more complex R programming concepts:

• Activity #01: Introduction to basic R syntax, variables, and arithmetic operations

  • Basic arithmetic operations
  • Variable assignment
  • Simple output formatting

• Activity #02: Advanced operations and control structures

  • Vector operations and comparisons
  • Type checking
  • Logical operations
  • Conditional execution

• Activity #03: Vector manipulation and iterative operations

  • Loop structures (repeat, for, while)
  • Vector calculations
  • Filtering and transformation

• Activity #04: Complete data collection, categorization, and analysis

  • User input processing
  • Data categorization
  • Aggregation and summary statistics

🚀 Setup and Installation

1. Install R:

   • Download and install R from The Comprehensive R Archive Network (CRAN)

2. Install RStudio:

   • Download and install RStudio Desktop from Posit

3. Clone the Repository:

   git clone https://github.com/akosikhada/R-programming-compilation.git
   cd R-programming-compilation

🔍 Usage

Each activity folder contains R scripts that can be executed in RStudio:

1. Open the script in RStudio:

   • Navigate to the activity folder
   • Open the desired .r file

2. Run the script:

   • Use the source() function: source("filename.r")
   • Alternatively, select and run code sections using the Run button or Ctrl+Enter (Cmd+Enter on Mac)

3. Follow prompts:

   • Some scripts require user input. Follow the prompts in the console

👨‍💻 Developer/s

Miguel Enrique Dasalla Developer