Real-estate-case-study

Problem Statement:

Consider that a real estate company has the data of real-estate prices in Delhi. The company wants to optimise the selling price of the properties, based on important factors such as area, bedrooms, parking, etc. Essentially, the company wants:

1. To identify the variables affecting house prices, e.g., area, number of rooms, bathrooms, etc.
2. To create a linear model that quantitatively relates house prices with variables, such as the number of rooms, area, number of bathrooms, etc.
3. To know the accuracy of the model, i.e. how well do these variables predict the house prices.

So this makes interpretation is important!