Linear Regression is about fitting a straight line from the scatter plot,key challenge here what constitutes a best fit line in other words what would be best values of and . The general idea is to find a line ( its coefficients) such that total error is at the minimum. There is a standard explanation that we need to minimize the total square error, which means we have to solve a minimization problem to solve optimal values of the coefficients. Obviously this method involves quite a lot of mathematics or calculus etc. which would not provide any institution or illustration, instead we will use a little of vector algebra and associated geometry to build the intuition about the solution.