compute simple linear regression equation

Linear regression calculators determine the line-of-best-fit by minimizing the sum of squared error terms (the squared difference between the data points and the line). While it is possible to calculate linear regression by hand, it involves a lot of sums and squares, not to mention sums of squares! So if you're asking how to find linear regression coefficients or how to find the least squares regression line, the best answer is to use software that does it for you.

Variables (not components) are used for estimation Have a look at our analysis checklist for more information on each: If you're thinking simple linear regression may be appropriate for your project, first make sure it meets the assumptions of linear regression listed below. The formula for simple linear regression is Y = mX + b, where Y is the response (dependent) variable, X is the predictor (independent) variable, m is the estimated slope, and b is the estimated intercept.

Linear regression is one of the most popular modeling techniques because, in addition to explaining the relationship between variables (like correlation), it also gives an equation that can be used to predict the value of a response variable based on a value of the predictor variable.

Compute simple linear regression equation