COVID-19 Data Analysis

A comprehensive analysis of COVID-19 trends using Johns Hopkins CSSE data, examining global patterns, US state-level variations, and statistical correlations between case and death rates.

Overview

This project analyzes COVID-19 data to answer key questions about pandemic trends, per-capita impacts across countries and US states, and correlations between case and death rates.

Key Findings

• Exponential growth patterns in US cases and deaths
• Significant state-level variations in per-capita impacts
• Strong positive correlation (R² = X.XX) between case and death rates
• Identification of states that performed better/worse than predicted

Data Sources

• Johns Hopkins CSSE COVID-19 Time Series Data
• Population lookup tables from the same repository

Analysis Structure

1. Data import and cleaning
2. Transformation to tidy format
3. State and country-level aggregation
4. Visualization of trends and comparisons
5. Statistical modeling and correlation analysis

Files

• Covid19_data_analysis.Rmd - Main analysis notebook
• Covid19_data_analysis.html - Knitted output
• Plots - Generated visualizations
• Data source containg all csv files - Data documentation

Requirements

• R 4.0+
• tidyverse, janitor, lubridate, ggplot2

Usage

1. Clone the repository
2. Open Covid19_data_analysis.Rmd in RStudio
3. Run all chunks to reproduce the analysis