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Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
say i have a function given by \[f(x)=\frac{v_1+v_2(v_3^3)}{YG}\]
 one year ago

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@JenniferSmart1 @jim_thompson5910
 one year ago

JenniferSmart1 Group TitleBest ResponseYou've already chosen the best response.0
for what class is this?
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
physics 2.. if i have 3 different avg velocities v1,v2 and v3 and \[U_t,U_d,U_Y,U_G\]
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
should i find the uncertainty of each velocity? that would seem to give a rounding error though =/
 one year ago

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or would i go about with substituting in \[v=\frac{d}{t}\]
 one year ago

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@Jemurray3
 one year ago

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@TuringTest
 one year ago

JenniferSmart1 Group TitleBest ResponseYou've already chosen the best response.0
@JamesJ
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
if i switch to d/tdw:1360620787006:dw
 one year ago

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dw:1360620861233:dw
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
then would i do for d1,t1,d2,t2,d3,t3,Y,and G?
 one year ago

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using partials of course
 one year ago

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dw:1360620933162:dw
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
then using \[TUnc_{f(x)}=\sqrt{(\frac{\delta f}{\delta d_1}U_d})^2+(\frac{\delta f}{\delta t_1}U_t)^2+(\frac{\delta f}{\delta d_2}U_d)^2....\]... i feel you'd get strange units doing this =/
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
but mayben ot since the other v terms cancel out in each partial
 one year ago

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any luck turing?
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
my other idea was to find the uncertainties of each velocity, and then use those uncertainties in my final uncertainty but that would seem to set me up for round errors = not so accurate
 one year ago

TuringTest Group TitleBest ResponseYou've already chosen the best response.0
Can't say I can really help here, sorry :(
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
derp lol
 one year ago

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@jim_thompson5910
 one year ago

Jemurray3 Group TitleBest ResponseYou've already chosen the best response.0
Yes, you're right. Generally speaking, if you have a function of a bunch of variables \[ f = f(x_i) \] Then the uncertainty in f is \[\sigma_f^2 = \sum_i \left(\frac{\partial f}{\partial x_i}\right) ^2\sigma_{x_i}^2\] This is true only if the variables xi are uncorrelated. If there is correlation between them, you must go to higher order error terms, but in this case that does not appear to be necessary.
 one year ago

Outkast3r09 Group TitleBest ResponseYou've already chosen the best response.0
@jemurray3 so in other words i should do d1 d2 d3 partials and t1 t2 t3 partials
 one year ago

Jemurray3 Group TitleBest ResponseYou've already chosen the best response.0
I don't see those variables in the expression you wrote. Whatever variables your function depends on, take the partials, multiply by the uncertainties, square them, and add them all up.
 one year ago
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