What Does Ordinary Least Squares Regression (OLSR) Mean?
Ordinary least squares regression (OLSR) is a generalized linear modeling technique. It is used for estimating all unknown parameters involved in a linear regression model, the goal of which is to minimize the sum of the squares of the difference of the observed variables and the explanatory variables.
Techopedia Explains Ordinary Least Squares Regression (OLSR)
Invented in 1795 by Carl Friedrich Gauss, it is considered one of the earliest known general prediction methods. OLSR describes the relationship between a dependent variable (what is aimed to be explained or predicted) and its one or more independent variables (explanatory variable). OLSR application can be found in myriad fields such as psychology, social sciences, medicine, economics and finance.
