This simple multiple linear regression calculator uses the least squares method to find the line of best fit for data comprising two independent *X* values and one dependent *Y* value, allowing you to estimate the value of a dependent variable (*Y*) from two given independent (or explanatory) variables (*X _{1}* and

The line of best fit is described by the equation ŷ = *b _{1}X_{1}* +

To begin, you need to add data into the three text boxes immediately below (either one value per line or as a comma delimited list), with your independent variables in the two *X* Values boxes 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, weight and shoe size, allowing you to predict shoe size on the basis of a person's height and weight, then height and weight would be your independent variables (*X _{1}* and

This multiple regression calculator can estimate the value of a dependent variable (*Y*) for specified values of two independent predictor variables (*X _{1}* &

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

Predictor *X1*

Predictor *X2*