Estimating The Error In Fit Parameters

This is a very quick introduction to finding the error in fit parameters as well as the propagation of error in measurement to the error in calculated results.

[mgahbelal]

I measured the flow rate 'Q' versus the pressure drop 'dP' curve for some experimental setup. Each parameters has an experimental error. I would like to make a polynominal or a power fit of the data using the averages values, dP=aQ^2+bQ+c, or dP=aQ^b. How can I calculate the error of the fit due to the error in both dP and Q?

[peterbrehmj]

Great Video, Thanks for putting this together.
I'm a little confused as to why you don't include altitude in the sigma_g equation.
(sigma_g/g)^2 = (2sigma_t/tvals)^2 + (sigma_h/h)^2 + (sigma_y/yvals)^2.
The conclusion is that altitude is very small with relatively large uncertainty, yet, altitude wasn't in the sigma_g equation, or in the original equation for g = 2*h/t^2. So it seems by definition, we're not going to see an effect of altitude on g.

[peterbrehmj]

At around 3:50, when you multiply g by the uncertainty (~1/16) what g are you using? The calculated g from measurements gm = 9.77 or the actual value of g = 9.81
I ask because 9.81/16 = 0.613 and 9.77/16 = 6.104. It may be a typo unless im really missing thing.

[ezgrxvb]

If I know the error associated with each mesure, shouldn't I create a normal distribution for each mesure with the associated error and then make the fit ? Why should I use the fit value of g instead of the mesured one ?