User849483 said:
Forgot to mention, but I am attempting to find the velocity at which a hollow cylinder with a particular inner radius will roll down an incline plane
Ok, I misunderstood your need. In post #1 I thought you wanted to find how uncertainties in the radius values combine to form uncertainty in v.
There are several common situations.
In one, you have a single set of inputs with an estimate for the error in each, and you want an estimate for the error in the output.
In another, you have multiple sets of inputs which are in principle the same, no estimate for the error in each, and you want an estimate for the error in the mean output.
You now seem to be saying that your case is this: you have multiple sets of inputs and outputs in which the output and one input vary, you possibly have
a priori estimates for the error in each, and you want an estimate for the error in the slope relating the variable input to the output.
That does seem strange because it means your equation is really $$v=k\sqrt{\frac{gh}{\frac{1}{2}+\frac{ r_o^2+r_i^2}{r_o^2} }}$$
and you want to find k and assess the error in that value. That is strange because you know k=1. So now I don’t know what you are trying to do, but if that is right, read on:
With no
a priori estimates for the input or output errors, you can use
https://saturncloud.io/blog/how-to-calculate-slope-and-intercept-error-of-linear-regression/.
If you have
a priori estimates for the input and output errors you should in principle be able to do better, but I have never found a general method that handles that.
At a guess, your greatest source of experimental error is in measuring the velocity.