devikadesai27/ghana-agricultural-profit-analysis

Analyzed Ghana Living Standards Survey (GLSS) data by cleaning, merging, and transforming multiple datasets, conducting exploratory data analysis, and building regression models to identify how education, employment, and local area characteristics influence agricultural profits. # 📊 Agricultural Profit Analysis in Ghana Statistical analysis of the **Ghana Living Standards Survey (GLSS)** to examine how **education attainment, employment, and local area characteristics** influence agricultural profit. This project includes data cleaning, exploratory data analysis (EDA), regression modeling, and model diagnostics using **R**. --- ## 🎯 Project Objectives - Clean, merge, and prepare multiple GLSS datasets for analysis. - Explore relationships between agricultural profit and key explanatory variables. - Build regression models to evaluate factors affecting agricultural profit. - Assess model performance using diagnostic plots. --- ## 🛠️ Tools & Technologies - R - RStudio - Data Cleaning & Transformation - Exploratory Data Analysis (EDA) - Regression Analysis - Statistical Modeling --- ## 📂 Repository Structure ``` ├── code/ # R scripts ├── Figures/ # EDA and regression figures ├── figures/ # Additional visualizations ├── community/diagnostics/ # Model diagnostic plots ├── *.README # Documentation for each project stage ├── dtc-dtc-1.Rproj # RStudio project └── README.md ``` --- ## 📈 Project Workflow ### Data Preparation - Cleaned, transformed, and merged multiple GLSS datasets. - Created an analysis-ready dataset. ### Exploratory Data Analysis - Examined distributions, correlations, and relationships among variables. ### Regression Analysis - Built pooled log-profit regression models. - Evaluated model assumptions using diagnostic plots. --- ## 🚀 How to Run 1. **Clone the repository** ```bash git clone github.com ``` 2. **Open the project** - Launch **RStudio**. - Open the `dtc-dtc-1.Rproj` file. 3. **Run the analysis** - Execute the R scripts in the `code/` folder. - Refer to the README documentation files for each stage of the workflow. - Review the figures and diagnostic plots in …