Experiment with angular acceleration

AI Thread Summary
The discussion centers on determining the best estimation of angular acceleration from an experiment involving a rotating cylinder and a dropping weight. The experimenter has calculated an average angular acceleration weighted by uncertainties but is unsure how to quantify the uncertainty of this average. They seek clarification on the correct method for calculating the uncertainty associated with the estimated angular acceleration. The conversation references the concept of mean squared error as a potential approach to address this uncertainty. Understanding how to properly calculate and interpret these uncertainties is crucial for accurate results in classical mechanics experiments.
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I'm not sure if this goes in there since it's a question about an experiment involving classical mechanics.
So I've done an experiment where I have determined for a rotating cylinder, its angular acceleration as I let a weight attached to it drop. Now each of these angular accelerations have an uncertainty, and I want to figure out the best estimation for the angular acceleration. What I did was to make an average over the angular acceleration weighted over their uncertainties. This is correct right? - I'm pretty sure, that's how it's done.
My problem is however, that I now don't know how to figure out the uncertainty for this estimated angular acceleration - how do I do that?
 
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Now each of these angular accelerations have an uncertainty, and I want to figure out the best estimation for the angular acceleration.

After this, I don't know what your explanation(s) means.

one approach:


http://en.wikipedia.org/wiki/Mean_squared_error
 

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