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Analyse a Housing Dataset of Usa for predicting housing prices for regions in the USA

License: Apache License 2.0

Python 100.00%
pandas sklearn python matplotlib-pyplot numpy seaborn

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Linear-Regression-Prediction-Project-part-2

Analyse a Housing Dataset of Usa for predicting housing prices for regions in the USA

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Avg. Area Income 21.528276 Avg. Area House Age 164883.282027 Avg. Area Number of Rooms 122368.678027 Avg. Area Number of Bedrooms 2233.801864 Area Population 15.150420

Interpreting the coefficients:

Holding all other features fixed, a 1 unit increase in Avg. Area Income is associated with an *increase of $21.52 *. Holding all other features fixed, a 1 unit increase in Avg. Area House Age is associated with an *increase of $164883.28 *. Holding all other features fixed, a 1 unit increase in Avg. Area Number of Rooms is associated with an *increase of $122368.67 *. Holding all other features fixed, a 1 unit increase in Avg. Area Number of Bedrooms is associated with an *increase of $2233.80 *. Holding all other features fixed, a 1 unit increase in Area Population is associated with an *increase of $15.15 *.

Reference Material:https://www.udemy.com/share/101WaUB0scc1dQR34=/

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