A Study on Housing Price Prediction: Determinants and Effects

This study explores key factors that influence housing prices and assesses their impact on property valuation. By analysing a range of attributes such as area, number of bedrooms and bathrooms, stories, presence of air conditioning, basement, parking, and proximity to preferred areas the project aims to build predictive models for accurate pricing. The study uses sample of 500 house prices from Kaggle datasets and makes use of statistical and machine learning techniques, including multiple regression analysis, this research identifies significant predictors and quantifies their effect on house prices. The study provides insights into how property features offers useful information for buyers, sellers, and real estate professionals.