**Least**Squares Mean. This is a mean estimated from a linear model. In contrast, a raw or arithmetic mean is a simple average of your values, using no model.

**Least**squares

**means**are adjusted for other terms in the model (like covariates), and are less sensitive to missing data.

Then, what is the principle of least squares?

The

**least squares principle**states that the SRF should be constructed (with the constant and slope values) so that the sum of the**squared**distance between the observed values of your dependent variable and the values estimated from your SRF is minimized (the smallest possible value).What is least square analysis?

The

**method**of**least**squares is a standard approach in regression**analysis**to approximate the solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns.What does it mean when the regression line is the least squares?

A

**regression line**(LSRL -**Least Squares Regression Line**) is a straight**line**that describes how a response variable y changes as an explanatory variable x changes. The**line**is a mathematical model used to predict the value of y for a given x.**Regression**requires that we have an explanatory and response variable.