Homoskedastic refers to a condition in which the variance of the error term in a regression model is constant. Learn more about its importance and how it is used.

There are rarer instances, for example, an example from geology discussed here, where the use of orthogonal regression without proper attention to modeling may lead to either overcorrection or ...

In this video, we will learn what is linear regression in machine learning along with examples to make the concept crystal clear.

That is another problem to solve and needs different approaches if you have them. Building a linear regression model So far, I have explored the dataset in detail and got familiar with it.