Regression and Ordinary Least Square Method Depth Analysis :

Definition of Ordinary Least Square:

Ordinary Least Square means the reducing or minimizing the sum of squared errors which is also known as sum of squared residuals. 

What is meant by errors in Linear Regression ?

Errors are defined as difference between observed and predicted value of the data. In OLS (Ordinary Least Square), we square the value of each error to remove the negative value and overall SSE should be minimum to get the best fit line in the linear regression 

Formulas for calculating the best fit line : 

Business Case :

Identify the salary based on the errors using Regression Statistical Method through Microsoft Excel.