About Project

This House Price Regression Analysis project applies multiple linear regression in R to identify the key factors influencing housing prices. The study includes exploratory data analysis, assumption testing, response transformation, variable selection using BIC and AIC, and model comparison. The final model highlights the most significant predictors of price while maintaining interpretability and statistical robustness. This project demonstrates advanced statistical modeling, diagnostic testing, and data-driven decision-making using R.