rehammohamed2022-sys/Statistical-Analysis-of-Egyptian-Wheat-Farming

Statistical analysis of wheat productivity, post-harvest losses, and farm profitability in Egypt using quantile regression, logistic regression, and machine learning techniques in R. Statistical Analysis of Egyptian Wheat Farming Graduation Project Faculty of Economics and Political Science Cairo University Overview This graduation project investigates the key factors affecting wheat productivity, post-harvest losses, and farm profitability among Egyptian wheat farmers. The study applies statistical and econometric methods to identify the determinants of agricultural performance and provide evidence-based insights that can support agricultural development and policy planning in Egypt. Research Objectives * Identify the determinants of wheat yield among Egyptian farmers. * Analyze the factors associated with high post-harvest wheat losses. * Examine the relationship between production costs and farm profitability. * Provide policy recommendations to improve productivity and reduce losses. Statistical Methods * Exploratory Data Analysis (EDA) * Pearson Correlation Analysis * Kernel Density Estimation * Quantile Regression * Binary Logistic Regression * ROC Curve Analysis * Model Diagnostics * AIC-Based Variable Selection Software * R * RStudio Key Findings Wheat Productivity * Pesticide investment was the most consistent predictor of wheat yield. * Water source had different effects across productivity levels. * Seed investment became particularly important among high-yield farmers. * Crop damage and fallow land negatively affected productivity among top-performing farms. Post-Harvest Losses * Farmers relying on rain-fed agriculture were substantially more likely to experience high post-harvest losses. * Seasonal accidents significantly increased loss risk. * Access to market-based agricultural inputs reduced the likelihood of high losses. Farm Profitability * Farm profitability was influenced by production costs and cost structure. * Statistical modeling identified key factors associated with profitable and unprofitable farms. Skills Demonstrated * Statistical Modeling * Applied Econometrics * Quantitative Research * Data Anal …