This assignment analyzes what factors predict whether a home in the Ames dataset falls into the high-price category. Using dummy variables, the Linear Probability Model, and logistic regression, I examine how features such as living area, quality, garage capacity, central air, and neighborhood influence the probability of a home being high price. The models are compared, interpreted, and tested using a 75/25 train–test split to evaluate predictive performance and real-world applicability.

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