What is the best method for plotting function parameter errors?

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Hi, suppose that you have some function: [itex]F(x;a)[/itex]
where [itex]x[/itex] is the variable with which you plot the function and [itex]a[/itex] is some parameter which enters the function.
If I want to find the error coming from some uncertainty in [itex]a[/itex], computationally, I would have to plot the function for 2 different let's say values of [itex]a[/itex]: Let's say that this means to plot the functions below:
[itex]F(x;a)[/itex]
[itex]F(x;2a)[/itex]
Then I believe the error then can can be computed by (their difference):

[itex]F(x;2a)-F(x;a)[/itex]

as well as (their fluctuation)

[itex]\frac{F(x;2a)-F(x;a)}{F(x;a)}[/itex]

Which of these two are best for a plotting? Is there some physical meaning behind any of these two? like they are showing something different to the reader?
 
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I think what you're after is to "portray" the "error" visually, not to compute it. For such a purpose, I'd pefer to see a shaded graph created by plotting lots of curves on top of each other The reason is that the points on the the graphs of [itex]F(x,a)[/itex] and [itex]F(x,2a)[/itex] might not show the most extreme values. For example, it's possible that that for some [itex]a < c < 2a[/itex] that [itex]F(x,c)[/itex] might be be greater than both [itex]F(x,a)[/itex] and [itex]F(x,2a)[/itex]. If you're sure that this kind of thing won't happen then then your idea of plotting only [itex]F(x,a)[/itex] and [itex]F(x,2a)[/itex] would be sufficient.

You haven't defined what you mean by "error". If the graph is to portray a specific statistical meaning, we'd have to know the probability model for the situation.
 
By error I mean something like this: in general you can't determine [itex]a[/itex] exactly, but within some range [itex](a_{min}, a_{max})[/itex]... This will cause an error to the function [itex]F(x;a)[/itex] coming from [itex]a[/itex]...
So I thought :
I could determine it by eg saying that I can determine [itex]a[/itex] within an order of magnitude (let's say [itex]10 \le a \le 100[/itex]), what should I do to see the error then? I would have to plot [itex]F(x;10)[/itex] and [itex]F(x;100)[/itex] and look at their differences...
 
ChrisVer said:
I would have to plot [itex]F(x;10)[/itex] and [itex]F(x;100)[/itex] and look at their differences...

That would be Ok if the graph of [itex]F(x,c)[/itex] always rises as [itex]c[/itex] increases or always falls as [itex]c[/itex] increases. But suppose as [itex]c[/itex] increases between 10 and 100, the point at [itex]F(5,c)[/itex] moves up and down. Then [itex]F(5,10)[/itex] and [itex]F(5,100)[/itex] might not indicate the extremes of the movement.

What specific [itex]F(x,a)[/itex] are you dealing with?
 
Recombination (cosmology) and the uncertainty in determining the recombination temperature [itex]T[/itex] in which [itex]X(T_{rec})= \frac{n_{ion}}{n_e}=1/2[/itex]
http://www.maths.qmul.ac.uk/~jel/ASTM108lecture8.pdf
(Eq. 8.23 with uncertainty in [itex]\eta =\frac{n_B}{n_\gamma}= 4 - 8 \times 10^{-10}[/itex] )
 
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ChrisVer said:
(Eq. 8.23 with uncertainty in [itex]\eta =\frac{n_B}{n_\gamma}= 4 - 8 \times 10^{-10}[/itex] )

[itex]\frac{ n_{ion}}{n_e} = \frac{n_\gamma}{n_B} \ exp( \frac { E_{ion}} {k_B T} ) \ \[/itex] (Eq.8.23)

[itex]T = \frac{E_{ion}}{k_B} \frac{1}{ \ln({\frac{n_{ion}}{n_e})} \ - \ \ln({ \frac{n_\gamma}{n_B} )} }[/itex]

[itex]T = \frac{E_{ion}}{k_B} \frac{1}{ \ln({\frac{n_{ion}}{n_e})} \ - \ \ln({ \frac{1}{\eta} )} }[/itex]

So you are plotting this as [itex]y = T = f(x,a)[/itex] with [itex]a = \eta[/itex]. But what variable plays the role of [itex]x[/itex] ?
 
ehmm.. no, I am plotting [itex]X \equiv X(T ;\eta)= \frac{1}{\eta} \exp \Big ( \frac{E_{ion}}{k_BT} \Big)[/itex] for [itex]3000<T(Kelvin)<4500[/itex]
And [itex]\eta= 4 \times 10^{-10}[/itex] and [itex]\eta= 8 \times 10^{-10}[/itex]
However I'd [personally] like to generalize this to an uncertainty of [itex]\eta[/itex] within an order of magnitude...
 
Then for a given value of [itex]T[/itex] , the point on the graph, as a function of [itex]\eta[/itex] has the form [itex]y = s \frac{1}{\eta}[/itex] where [itex]s[/itex] is a constant. So I plotting points given by the extreme values of [itex]\eta[/itex] will show the extremes of variation in [itex]y[/itex].