Agyemang1z/Election-Forensics

R codes for research work on "Baseline Comparative Analysis and Review of Election Forensics: Application to Ghana's 2012 and 2020 Presidential Elections" # Baseline Comparative Analysis and Review of Election Forensics Applied to Ghana Presidential Elections ## Overview This repository contains R code for election forensics analysis applied to Ghana presidential election data from 2012 and 2020. The project is designed to support reproducible statistical diagnostics and comparative analysis in electoral data integrity research. ## Repository - **Repository name:** `Election-Forensics` - **Repository type:** R election forensics repository - **Repository link:** github.com - **Primary author:** Edmund Fosu Agyemang - **Academic identifier:** ORCID: orcid.org ## Repository Contents The public repository listing identifies the following files: - `Election Forensics.R` - `README.md` ## Research Objectives - Apply election forensics methods to Ghana presidential election data. - Compare patterns across the 2012 and 2020 elections. - Generate descriptive and statistical diagnostics relevant to electoral data integrity. - Provide reproducible R code for methodological transparency. ## Analytical Workflow 1. Place election data files in the repository directory if they are not already included. 2. Load the required election dataset into R. 3. Run descriptive summaries and visualization routines. 4. Apply election forensics diagnostics as implemented in the R script. 5. Compare results across the selected election years. 6. Interpret findings cautiously within the limits of statistical forensics. ## Software Requirements Recommended software and packages include: - R 4.3 or later - RStudio recommended - tidyverse - ggplot2 - readr - dplyr ## Reproducibility Guide Run the project from a clean working directory. The following commands provide a suggested starting point: ```bash git clone github.com cd Election-Forensics R install.packages(c("tidyverse", "ggplot2", "readr", "dplyr")) source("Election Foren …