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Real Estate... by ui149029 is a document available to read on EtoBox.

This project analyzes a dataset of 105 residential properties to explore the relationship between house price, square footage, house age, and number of bedrooms. The findings indicate that square footage is the most significant predictor of house price, with a regression model explaining 96% of the price variation. The study concludes that each additional square foot increases the house price by approximately $160, making the model a practical tool for property valuation.

Author
ui149029
Language
EN