Ordinary Least Squares (OLS) estimation is a statistical method used to estimate the coefficients of a linear regression model.

In linear regression, we aim to find the best-fitting line (or hyperplane in the case of multiple linear regression) that represents the relationship between the dependent variable and one or more independent variables.

OLS is a way to determine the values of the coefficients that provide the closest match between the model’s predictions and the observed data.