Assumptions of linear regression?

[vishrut-singhal]

There are four assumptions associated with a linear regression model:

1. Linearity : The relationship between X and the mean of Y is linear.
2. Homoscedasticity : The variance of residual is the same for any value of X.
3. Independence : Observations are independent of each other.
4. Normality : For any fixed value of X, Y is normally distributed.

[chirag-garg]

Linear Regression is a machine learning algorithm based on a supervised ml task to compute the regression coefficients. Regression models a target prediction based on independent variables.

1. Linearity
2. No Endogeneity
3. Normality
4. Homoscedasticity
5. No autocorrelation
6. No multicollinearity