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Ames Housing — Continuous Outcome Drivers In Minutes

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What's in the report?

Applies random forest regression to 82 property features (lot dimensions, condition ratings, area measurements, neighborhood, and structural attributes) to predict SalePrice. Permutation-based feature importance identifies the top drivers, while partial dependence and residual analysis surface non-linear relationships and model fit diagnostics.

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Distribution of Home Sale Prices

Interactive bar visualization

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Top Predictors of Sale Price

Interactive table visualization

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Price Response to Overall Quality

Interactive bar visualization

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Price Response to Living Area

Interactive scatter visualization

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Price Trend by Year Built

Interactive line visualization

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Model Residuals: Fitted vs. Residuals

Interactive scatter visualization

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AI Insights

Plain-English interpretation of what the numbers mean, what's significant, and what to do next.

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See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.

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