To Regress X On Y. It permits the prediction of the most probable values of y Familiarity information. This code will give you the two-parameter output you expect.
We could also write that weight is -31686697height. Avoid Mouse Pointer from the video. If y is the response and x is the explanatory variable its regress y on x.
The regression equation of our example is Y -31686 697X where -36186 is the intercept a and 697 is the slope b.
You dont show us your code but I am guessing you neglected to add a column of ones to your x input as described in the documentation. The regression of X on Y is not the same as the regression of Y on X. It is customary to talk about the regression of Y on X hence the regression of weight on height in our example. Learn more about regression Statistics and Machine Learning Toolbox.
