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Problem Statement

A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.

They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the American market, since those may be very different from the Chinese market.

Dataset

The dataset used is the Car Prediction from Kaggle. The task Regression modelling to find relation between dependent(target="price") to the independent variable.

If the task is a regression task, then explain the target variable and give brief statistics.(e.g. Housing Prices)

Target Variable: Price

Sale Price refers to the selling price of the car.
Mean Selling Price: 13,276.71 $
Max Selling Price: 45,400 $
Min Selling Price: 5,118 $

Model(s) Used

Linear regression is one of the ways to perform predictive analysis. It is used to examine regression estimates.
To predict the outcome from the set of predictor variables Which predictor variables have maximum influence on the outcome variable? The regression estimates explain the relationship between one dependent variable and one or more independent variables. The same is represented in the below equation.
y=mx+c
x: Score of the independent variable
m: Regression coefficient
c: Constant
x: Independent variable

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Car Price Prediction

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