How to Calculate Final Uncertainty in Quotient Calculations?

In summary, on the homework question, there is always uncertainty associated with a physical measurement, but we were not told what the uncertainty of 40000 was, and we didn't have any means of finding it out during the experiment. So in this case what would be the best thing to do?
  • #1
roam
1,271
12

Homework Statement



This is about experimental physics. I have a value of resistance [tex]R=9000 \pm 1000[/tex]. Then I had to do the following calculation:

[tex]\frac{40000}{9000}=4.44 \ \Omega[/tex]

So, I'm not quite sure how to calculate the final uncertainty from my uncertainty [tex]\sigma = \pm 1 \ k\Omega[/tex]


The Attempt at a Solution



Since [tex]9000 \times (4.8 \times 10^{-4}) = 4.44[/tex]

I used the rule that says [tex]y=na \implies \sigma_{y}=n \sigma_a[/tex]

so:

[tex]\sigma = 1000 \times (4.8 \times 10^{-4}) = 0.48 \ \Omega[/tex].

Is this correct? Would the final uncertainty be ±0.48? :confused:
 
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  • #2
I don't know any formal math on this, but if you start off with an uncertainty of +/- 11%, how can you not end up with an uncertainty of +/- 11% ?
 
  • #3
Hi roam!

Yes, this is correct.

When multiplying or dividing the relative error remains the same.Generally we have for a quotient q = x/y
that the contribution in its uncertainty by y is:

[tex]\Delta q = | \frac {\partial q} {\partial y} | \Delta y = |\frac {-x} {y^2}| \Delta y = |q| \cdot |\frac {\Delta y} y|[/tex]Note however that in your answer there should also be a contribution of the uncertainty of 40000. Or doesn't it have an uncertainty?
 
  • #4
I like Serena said:
Hi roam!

Yes, this is correct.

When multiplying or dividing the relative error remains the same.


Generally we have for a quotient q = x/y
that the contribution in its uncertainty by y is:

[tex]\Delta q = | \frac {\partial q} {\partial y} | \Delta y = |\frac {-x} {y^2}| \Delta y = |q| \cdot |\frac {\Delta y} y|[/tex]


Note however that in your answer there should also be a contribution of the uncertainty of 40000. Or doesn't it have an uncertainty?

I think there is always uncertainty associated with a physical measurement. But we were not told what the uncertainty of 40000 was, and we didn't have any means of finding it out during the experiment. So in this case what would be the best thing to do?
 
  • #5
roam said:
I think there is always uncertainty associated with a physical measurement. But we were not told what the uncertainty of 40000 was, and we didn't have any means of finding it out during the experiment. So in this case what would be the best thing to do?

For a homework question I think it is ok.In practice you'd have to apply a rule of thumb.

If it's uncertainty is much lower, which would be typical for a physical constant, you can ignore it.

A measurement should always be given with its uncertainty.
If it isn't, the rule of thumb is that its uncertainty is 0.5 of the last digit.
In your case: 40000 +/- 5000.
Note that 40000 would usually be written as 4x104 or 4.0x104 to make the number of significant digits clear.EDIT: What do you mean that there were no means to find out during the experiment? There should always be a way.
 
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  • #6
I like Serena said:
For a homework question I think it is ok.


In practice you'd have to apply a rule of thumb.

If it's uncertainty is much lower, which would be typical for a physical constant, you can ignore it.

A measurement should always be given with its uncertainty.
If it isn't, the rule of thumb is that its uncertainty is 0.5 of the last digit.
In your case: 40000 +/- 5000.
Note that 40000 would usually be written as 4x104 or 4.0x104 to make the number of significant digits clear.


EDIT: What do you mean that there were no means to find out during the experiment? There should always be a way.

I'm sure there is a way to find out. The experiment was about AC bridge measurements. What I posted above is from an equation

[tex]R=\frac{R_2 \times R_3}{R_4}[/tex]

R4 was a variable resistor and I found its value to be 9 +/- 1 k Ohms. R2 and R3 were stable resistors each of them were [tex]200 \Omega[/tex]. But they didn't tell us the uncertainty associated with them and we didn't investigate it during the course of the experiment.

So how would you find (using your rule) the uncertainty for each of the 200 Ohm resistors (0.5 of the last digit)? :confused:
 
  • #7
roam said:
I'm sure there is a way to find out. The experiment was about AC bridge measurements. What I posted above is from an equation

[tex]R=\frac{R_2 \times R_3}{R_4}[/tex]

R4 was a variable resistor and I found its value to be 9 +/- 1 k Ohms. R2 and R3 were stable resistors each of them were [tex]200 \Omega[/tex]. But they didn't tell us the uncertainty associated with them and we didn't investigate it during the course of the experiment.

So how would you find (using your rule) the uncertainty for each of the 200 Ohm resistors (0.5 of the last digit)? :confused:

On each resistor the uncertainty is specified.
The resistor would have 4 colored bands, the first 3 specify the ohms, the fourth specifies the uncertainty (usually 5% or 10%).Opposed to this, the rule of thumb basically says that all the numbers that are given are assumed to be correct, but to assume no more digits. The uncertainty is the corresponding possible rounding error.

Here it would be 200 +/- 50 ohms.
 
  • #8
I like Serena said:
On each resistor the uncertainty is specified.
The resistor would have 4 colored bands, the first 3 specify the ohms, the fourth specifies the uncertainty (usually 5% or 10%).


Opposed to this, the rule of thumb basically says that all the numbers that are given are assumed to be correct, but to assume no more digits. The uncertainty is the corresponding possible rounding error.

Here it would be 200 +/- 50 ohms.


Yes, I knew that the fourth band corresponds to the tolerance of the resistor. But we were using decade resistance boxes, so I couldn't see any colour bands. And I don't know the specifications of those resistance boxes. So I'm just going to use the rule of thumb that you mentioned.

I also have one last question: if we have the value x=147 ± 10 (absolute uncertainty), and we calculate

[tex]\frac{1}{x}=\frac{1}{147} = 6.8 \times 10^{-3}[/tex]

How would you calculate the uncertainty here? The "1" here doesn't have any associated uncertainty, it's from the formula.
 
  • #9
I mean, in general when you have 1 over some number, what happens to the uncertainty of that number?
 
  • #10
roam said:
I mean, in general when you have 1 over some number, what happens to the uncertainty of that number?

"1" is not a measurement, it's a mathematical constant, and a whole number to boot.
Its uncertainty is zero.

Same for any mathematical constant (2, 3, pi, e, i, etcetera).
 
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  • #11
I like Serena said:
"1" is not a measurement, it's a mathematical constant, and a whole number to boot.
Its uncertainty is zero.

Same for any mathematical constant (2, 3, pi, e, i, etcetera).

Right. So does this mean that for the example I gave where x=147 ± 10, for 1/x the error will be

[tex]\sqrt{p_1+p_x^2}=\sqrt{0+p_x^2}[/tex]

where px is the percent error of x (i.e 10/147 * 100 = 6.8%). Is that right?
 
  • #12
roam said:
Right. So does this mean that for the example I gave where x=147 ± 10, for 1/x the error will be

[tex]\sqrt{p_1+p_x^2}=\sqrt{0+p_x^2}[/tex]

where px is the percent error of x (i.e 10/147 * 100 = 6.8%). Is that right?

I assume you meant to use the square of p1, instead of just p1.

Apparently you're already aware that you should add uncertainties squared and then draw the square root.
Good! :smile:

However, you have to do this with the absolute uncertainties and not with the relative uncertainties.
These are standard deviations, and the typical symbol (from statistics) to use would be σ instead of p.
In physical error analysis the typical symbol would be Δx.

EDIT: as a coincidence, in this particular example the results will come out the same! :wink:
 
  • #13
I like Serena said:
I assume you meant to use the square of p1, instead of just p1.

Apparently you're already aware that you should add uncertainties squared and then draw the square root.
Good! :smile:

However, you have to do this with the absolute uncertainties and not with the relative uncertainties.
These are standard deviations, and the typical symbol (from statistics) to use would be σ instead of p.
In physical error analysis the typical symbol would be Δx.

EDIT: as a coincidence, in this particular example the results will come out the same! :wink:

Well, 02=0 (since the uncertainty of a constant is 0 as you pointed out). Personally by the sigma (σ) I denote the absolute uncertainty whereas by "p" I mean the percentage uncertainty. For addition or subtraction of x and y, we have to add their absolute uncertainties in quadrature, i.e

√(σxy)

But for multipication or division we have to use the percent uncertainties:

√(px+py).

So, in my case I think I should use the percent uncertainty since there is a division! :)

Anyway, thank you very much for all the help, I really appreciate it.
 
  • #14
roam said:
Well, 02=0 (since the uncertainty of a constant is 0 as you pointed out). Personally by the sigma (σ) I denote the absolute uncertainty whereas by "p" I mean the percentage uncertainty. For addition or subtraction of x and y, we have to add their absolute uncertainties in quadrature, i.e

√(σx2y2)

But for multipication or division we have to use the percent uncertainties:

√(px2+py2).

So, in my case I think I should use the percent uncertainty since there is a division! :)

Anyway, thank you very much for all the help, I really appreciate it.

Yes, sorry, you're right.
In this case you need to square the relative uncertainties, add, and take the square root.

I meant that in the general case, you'll get contributions to the total uncertainty from different sources.
This is applicable for any formula.

To compare, in the case

[tex]q= \frac x y[/tex]

Your uncertainty is

[tex]\Delta q = \sqrt { (\Delta q_x)^2 + (\Delta q_y)^2 }[/tex]

where [itex]\Delta q_x = |\frac 1 y| \cdot \Delta x[/itex] and [itex]\Delta q_y = |\frac {-x } {y^2}| \cdot \Delta y[/itex].





Sorry if I'm overdoing it.
I guess you don't need this if you only do sums and quotients. ;)
(But what if you have square roots, or even worse, a sine? :wink:)
 
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  • #15
(But what if you have square roots, or even worse, a sine? :wink:)[/QUOTE]

RUN AWAY, well that's what i do anyway
 
  • #16
lackos said:
(But what if you have square roots, or even worse, a sine? :wink:)

RUN AWAY, well that's what i do anyway

:rofl:

So what about KE =½mv2?

You may want to know the uncertainty in that one, before it overtakes you and hits you while you're running away! :wink:
 
  • #17
I like Serena said:
Hi roam!

Yes, this is correct.

When multiplying or dividing the relative error remains the same.


Generally we have for a quotient q = x/y
that the contribution in its uncertainty by y is:

[tex]\Delta q = | \frac {\partial q} {\partial y} | \Delta y = |\frac {-x} {y^2}| \Delta y = |q| \cdot |\frac {\Delta y} y|[/tex]


Note however that in your answer there should also be a contribution of the uncertainty of 40000. Or doesn't it have an uncertainty?

The statement "When multiplying or dividing the relative error remains the same" is only true for small changes. In this case, 1000 is not particularly small compared with 9000, so the percentages when going up from 9000 to 10000 or down from 9000 to 8000 are different. Just calculate them to see.

RGV
 

What is the definition of "Propagation of Uncertainty"?

"Propagation of Uncertainty" refers to the mathematical process of determining the uncertainty in the result of a calculation that involves multiple variables with their own individual uncertainties.

Why is "Propagation of Uncertainty" important in scientific research?

Uncertainty is inherent in all measurements and calculations, and it is crucial to accurately account for this uncertainty in scientific research. "Propagation of Uncertainty" allows scientists to determine the reliability and accuracy of their results, and to make more informed decisions based on these uncertainties.

What are the main sources of uncertainty in scientific measurements?

The main sources of uncertainty in scientific measurements include random error (caused by factors outside of the experimenter's control), systematic error (caused by flaws in the measurement process), and limitations of the measuring instrument.

How is "Propagation of Uncertainty" calculated?

The "Propagation of Uncertainty" calculation involves using a mathematical formula to combine the individual uncertainties of the variables involved in a calculation. This formula takes into account the mathematical relationship between the variables and their respective uncertainties.

How can scientists minimize uncertainty in their experiments?

Uncertainty in scientific experiments can be minimized by using more precise measuring instruments, increasing the sample size, controlling experimental conditions, and conducting multiple trials. Additionally, using appropriate statistical analysis and applying the principles of "Propagation of Uncertainty" can help to reduce uncertainty in scientific research.

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