Linear Regression and Correlation

In statistics, a linear regression is an approach to model the relationship between a scalar dependent variable y and one or more explanatory variables denoted x, and the correlation is a statistical measurement that describes the dependence between both variables. .

This tool retrieves for the linear relationship between x and y values (the formula y= ax+b) and the Pearson correlation coefficient (r) that describes the degree that linear dependence.

To use this tool, just include in the form x values and the dependent variables y. Each value for x and y must be separated by a line break, and the same number of values for x and y are required.

Often, non-linear relationships between two variables are linealized by applying to x or y values their logaritm or squares. You may do it when required by checking the corresponding checkboxes.

Values for x:

Apply to x values
Log x
Values for y:

Apply to y values
Log y


Source code available at