A European used car dealer built a multiple linear regression model to predict the resale price of a used car based on its conditions and features.
The model with estimated coefficients is: Price= -1853.37 – 135.73 x Age + 12.74 x Weight + 39.27 x HP – 0.019 x KM + 16.44 x Quarterly_Tax + 1179.35 x Fuel_TypeDiesel + 2374.06 x Fuel_TypePetrol
Descriptions of the variables in the model: Price: Offer price in Euros Age: Age in months as of August 2004 Weight: Weight in kilograms HP: Horsepower KM: Cumulative kilometers on odometer Quarterly_Tax: Quarterly road tax in Euros Fuel_Type: Fuel type (Petrol, Diesel, CNG)
1.) Interpret the meaning of coefficient (+16.44) of variable Quarterly_Tax.
2.) Interpret the meaning of coefficient (+1179.35) of variable Fuel_TypeDiesel.
3.) Interpret the meaning of coefficient (-135.73) of variable Age.
The model is:
Price= -1853.37 – 135.73 x Age + 12.74 x Weight + 39.27 x HP – 0.019 x KM + 16.44 x Quarterly_Tax + 1179.35 x Fuel_TypeDiesel + 2374.06 x Fuel_TypePetrol
1)
In the given model,
Coefficient of variable Quarterly_Tax is +16.44
Its interpretation is that, for each unit increase in Quarterly_Tax, the Price will increase by 16.44
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2)
Coefficient of variable Fuel_TypeDiesel is +1179.35
Its interpretation is that, for each unit increase in Fuel_TypeDiesel, the Price will increase by 1179.35
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3)
Coefficient of variable Age is -135.73
Its interpretation is that, for each unit increase in Age, the Price will decrease by 135.73
A European used car dealer built a multiple linear regression model to predict the resale price...