Calculating a Least Squares Regression Line: Equation, Example, Explanation If you want a simple explanation of how to calculate and draw a line of best fit through your data, read on!

Geoffrey S. Watson, Linear Least Squares Regression, The Annals of Mathematical Statistics, Vol. 38, No. 6 (Dec., 1967), pp. 1679-1699 ...

In a general normal regression model, this paper first derives the least upper bound (LUB) for the covariance matrix of a generalized least squares estimator (GLSE) relative to the covariance matrix ...

The least-squares method of cost estimation involves using mathematical regression techniques to calculate the slope and intercept of the best-fit line for the costs used in estimation.

The line of best fit is an output of regression analysis that represents the relationship between two or more variables in a dataset.

Linear regression-based quantitative trait loci/association mapping methods such as least squares commonly assume normality of residuals.