I need help with uncertainty of a curve fit
I need help with uncertainty of a curve fit
(OP)
I'd like to know how I can find the uncertainty in "m" and "b", the two constants you get when you make a linear curve fit "y=mx+b".
I know there's a similar topic just below here
http://www
But it seems to be that the mean and standard deviation obtained through that method has the same units of "y". How would I find uncertainties that have the same units as "m" and "b"?
For example, say I'm curve fitting stress and strain data to get the Young's modulus of a material. How would I determine the uncertainty in the Young's modulus, in units of MPa?
Thanks in advance.
I know there's a similar topic just below here
http://www
But it seems to be that the mean and standard deviation obtained through that method has the same units of "y". How would I find uncertainties that have the same units as "m" and "b"?
For example, say I'm curve fitting stress and strain data to get the Young's modulus of a material. How would I determine the uncertainty in the Young's modulus, in units of MPa?
Thanks in advance.
Talk To Other Members
RE: I need help with uncertainty of a curve fit
Consider the equation y = mx
You get an uncertainty (via comparison of data) for the modelled vs. actual y. The resulting "uncertainty" in m would then be simply calculated by U(m) = U(y)/x where U() are the uncertainties (errors).
In a similar manner, one could calculate uncertainties for both m and b, by plugging in the calculated value for m, and calculating what deviation in b is required to give the correct y value, and vice versa for m.
RE: I need help with uncertainty of a curve fit
The textbook should then go further and show you how to use these quantities to estimate the variances associated with using your regression equation for predictions: V(y) and V(E(y)). Make sure you understand the subtle difference between these two.