Classic Multi Independent Variable problem

Steps I followed :

• Used scatter() from matplotlib to see the nature of data
• Then used Multiple Linear Regression Model using Scikit learn lib
• Finally Checked the predictor values by plotting graphs

Assumptions of a Linear Regression :

• Linear
• Homoscedasticity ( In statistics, a sequence or a vector of random variables is homoscedastic if all random variables in the sequence or vector have the same finite variance. )
• Multivariate Normality
• Independence of Error
• Lack of Multicollinearity

Mathematical Model :

y = b0 + b1x1 + b2x2 + ......

And here I was careful about Dummy Trap