In a linear regression plot, the straight line represents the best attempt to minimize the residual sum of squares between known or observed data points and the predicted data points.

What are standardized residuals? How do I calculate it? How do I use it and interpret it? What are its benefits? The answers to these questions and more can be found below. Overview: What Are ...

The residual sum of squares (RSS) is a statistical technique used to measure the variance in a data set that is not explained by the regression model.

One of the most versatile regression diagnostic methods is to plot the residuals r i against the predictors (x i, r i) and the predicted values (ŷ i, r i) ().When noise assumptions are met, these ...

This example performs a simple linear regression of SALES on PRICE, producing the same results as PROC REG or another SAS regression procedure. The mathematical form of the model estimated by these ...

If the variance of the errors around the regression line varies much, the regression model may be poorly defined. The opposite of homoskedasticity is heteroskedasticity (just as the opposite of ...

In our recent columns, we discussed how linear regression can be used to predict the value of a response variable on the basis of one or more predictor variables 1,2.We saw that even when a fit ...