What are the critical assumptions of linear regression?

There were three major critical assumptions that had to be made in linear regression. And they are given as:

It is vital to have a linear relationship among the independent and dependent. A scatter plot could be used for checking this fact. Scatter plot is a good way to determine relationships among continuous variables.

The independent variables in the dataset shall not exhibit any multicollinearity. In case they do, it shall be at the barest minimum. There should be a constraint on their value depending on the domain requirement.

Homoscedasticity is one of the most critical assumptions. It states that there should be an equal distribution of errors.