And this says well the probability if we would assume that is actually quite low. Regression Equation y a mx Slope m N x SXY - SX m SY m N x SX 2 - SX 2 Intercept a SY m - b SX m Where x and y are the variables. The mathematical formula for calculating the slope of known xs and know ys is.
The slope of a least squares regression can be calculated by m r SDySDx.
Look at the values of the parameters data set. In y mx b m is the slope and the point coordinate will contain both x and y. The parameter estimates will then have 3 values one for each group and you will need to create 3 macro variables for intercept and slope to reference in the inset statement. In this case where the line is given you can find the slope by dividing delta y by delta.