1. The problem statement, all variables and given/known data I have conducted an experiment which attempts to calculate the range of the visible light spectrum. Basically white light was shined through a diffraction grating (300 lines/mm) and diffraction theory is applied to calculate the wavelength. So, here are the variables: [tex]d=\frac{1}{300000}[/tex] [tex]l=0.20[/tex] [tex]\Delta l=0.001[/tex] [tex]y=0.043[/tex] [tex]\Delta y=0.005[/tex] 2. Relevant equations [tex]\sin\alpha=\frac{\lambda}{d}[/tex] [tex]\tan\alpha=\frac{y}{l}[/tex] 3. The attempt at a solution I combined these equations to end up with: [tex]\lambda=d\times\sin\left(\arctan\left(\frac{y}{l}\right)\right)[/tex] The problem is that I don't know how to estimate an uncertainty for this equation. I know that for simple equations like [tex]y=q\times r[/tex] the uncertainty is [tex]\Delta y=\left(\frac{\Delta q}{q}+\frac{\Delta r}{r}\right)\times y[/tex]. Unfortunately I don't know how to apply this to a more complex equation. If anyone could lead me in the right direction as to an equation which would give the uncertainty for [tex]\lambda=d\times\sin\left(\arctan\left(\frac{y}{l}\right)\right)[/tex], it would be greatly appreciated.
It can be done using calculus, if you've had calculus. But first I would get rid of the trig functions. What's an equivalent expression for sin(arctan(x)) ?
[tex]\frac{x}{x^{2}+1}[/tex] Substituting [tex]\frac{y}{l}[/tex] for [tex]x[/tex] gives: [tex]\frac{\frac{y}{\left|y\right|}\times l}{\sqrt{y^{2}+l^{2}}}[/tex] I hadn't thought of doing this, so it seems to be a step in the right direction. I have done limited calculus, I'm just finishing the first year of IB Math HL so we're starting on integration right now. I looked briefly at the wikipedia page for error propagation and didn't really understand it.
Hmm... yeah, Wikipedia is being ridiculously detailed about this. FYI, here's the usual case: if you have a function [tex]f(x, y, z)[/tex] and the uncertainties in the arguments are [tex]\delta x[/tex], [tex]\delta y[/tex], and [tex]\delta z[/tex], then the uncertainty in [tex]f[/tex] is [tex]\delta f = \sqrt{\left(\frac{\partial f}{\partial x}\delta x\right)^2 + \left(\frac{\partial f}{\partial y}\delta y\right)^2 + \left(\frac{\partial f}{\partial z}\delta z\right)^2}[/tex] Of course, there are some conditions on that formula, i.e. small, independent (uncorrelated) uncertainties and Gaussian distributions, but probably 99% of the time that formula is good enough.
OK, thanks for the help so far. I applied the above formula to my equation and received the following result: [tex]\delta f = \sqrt{{\delta l}^{2}\,{\left( -\frac{d\,\left| l\right| \,y}{{l}^{2}\,\sqrt{{y}^{2}+{l}^{2}}}+\frac{d\,y}{\left| l\right| \,\sqrt{{y}^{2}+{l}^{2}}}-\frac{d\,\left| l\right| \,y}{{\left( {y}^{2}+{l}^{2}\right) }^{\frac{3}{2}}}\right) }^{2}+{\delta y}^{2}\,{\left( \frac{d\,\left| l\right| }{l\,\sqrt{{y}^{2}+{l}^{2}}}-\frac{d\,\left| l\right| \,{y}^{2}}{l\,{\left( {y}^{2}+{l}^{2}\right) }^{\frac{3}{2}}}\right) }^{2}}[/tex] Substituting with the variables in my first post returns the result: [tex]\delta f = 7.79\times 10^{-8}[/tex] Which is exactly what I received when I tried using an online uncertainty calculator! Thank you so much!