This simple linear regression calculator uses the least squares method to find the line of best fit for a set of paired data, allowing you to estimate the value of a dependent variable (*Y*) from a given independent variable (*X*).

The line of best fit is described by the equation ŷ = *bX* + *a*, where *b* is the slope of the line and *a* is the intercept (i.e., the value of *Y* when *X* = 0). This calculator will determine the values of *b* and *a* for a set of data comprising two variables, and estimate the value of *Y* for any specified value of *X*.

To begin, you need to add *paired* data into the two text boxes immediately below (either one value per line or as a comma delimited list), with your independent variable in the *X* Values box and your dependent variable in the *Y* Values box. For example, if you wanted to generate a line of best fit for the association between height and shoe size, allowing you to predict shoe size on the basis of a person's height, then height would be your independent variable and shoe size your dependent variable).

This calculator can estimate the value of a dependent variable (*Y*) for any specified value of an independent variable (*X*). Simply add the *X* values for which you wish to generate an estimate into the Estimate box below (either one value per line or as a comma delimited list).

*Note*: If you *just* want to generate the regression equation that describes the line of best fit, leave the box below blank.

Estimate