Predictive Modelling and Statistical Analysis of Housing Prices in Lagos State, Nigeria

Abstract

This study delves into housing market analysis and price prediction, leveraging statistical modeling and machine learning techniques to uncover patterns and forecast property prices. The housing market is influenced by diverse factors such as location, property features, economic indicators, and market trends, necessitating a comprehensive analytical approach. Using a dataset comprising historical housing prices and relevant attributes, the study employs exploratory data analysis to identify key determinants of property values. The findings highlight significant predictors of housing prices and demonstrate the potential of predictive analytics in guiding buyers, sellers, and policymakers. This research offers valuable insights into market dynamics and contributes to data-driven decision-making in real estate