Calculating the Percentage Error in Measurement Uncertainties

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In summary: The Attempt at a SolutionThe plus-and-minuses don't cancel each other out. However, if x and y are measurements of properties X and Y and if x and y are dependent, then z=x+y. Taking z=xy, we have that \sigma_z^2=\sigma_x^2+\sigma_y^2.
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Nerd10
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Homework Statement


Let x=5.234+/-0.0005 and y=5.123+/-0.0005. Find the percentage error of the difference a=x-y when relative errors deltax=deltay=0.0001.

Homework Equations


I think a=0.111 because 5.234-5.123=0.111 and +/-0.0005 cancel each other out. But how do I find the answer from here?


The Attempt at a Solution

 
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  • #2
The plus-and-minuses don't cancel each other out.

Are x and y independent?
You must have done some theory of errors before now?

I prefer sigmas for standard errors:
$$\sigma_a^2=\sigma_x^2+\sigma_y^2\\ p_a=100\frac{\sigma_a}{a}$$
 
  • #3
Thanks.
 
  • #4
If x and y are measurements of properties X and Y, then we can represent uncertainties in the measurement process by writing: $$X=x\pm\sigma_x\qquad Y=y\pm\sigma_y$$.
When we do, we are basically saying that X and Y can be modeled as continuous random variables which are normally distributed with mean equal to their measured value and standard deviation equal to the uncertainty.

When you deal with them like that, then all that stuff you probably did in secondary school about hypothesis testing comes into play.

X and Y may have dependent of independent measurements.

If independent then:$$z=x+y\implies \sigma_z^2=\sigma_x^2+\sigma_y^2\\
z=xy\implies \left(\frac{\sigma_z}{z}\right)^2=\left(\frac{\sigma_x}{x}\right)^2+ \left( \frac{\sigma_y}{y}\right)^2$$note that ##x-y=x+(-y)## and ##x\div y = x\times (1/y)## so I don't need to provide specific rules for subtraction and division: the uncertainties part always adds.
BTW: If you think these rules look like Pythagoras - you are right.

If the measurements are dependent though - like we measure length y starting from where length x left off or we add/multiply a measurement to itself - then the rules get looser:$$z=x+y\implies \sigma_z=\sigma_x+\sigma_y\\ z=xy\implies \frac{\sigma_z}{z}=\frac{\sigma_x}{x}+\frac{\sigma_y}{y}$$

These are rules of thumb - from them, the others can be derived.
These rules come from a huge body of math that is often covered at senior undergrad and/or junior postgrad levels in science courses. Below that just remember the rules.
 

Related to Calculating the Percentage Error in Measurement Uncertainties

What is percentage error?

Percentage error is a measure of how inaccurate a measurement or calculation is compared to the actual or expected value. It is expressed as a percentage of the actual value.

How do you calculate percentage error?

The formula for percentage error is: (|Measured Value - Actual Value| / Actual Value) * 100%. This will give you the percentage difference between the measured value and the actual value.

What is a positive percentage error?

A positive percentage error means that the measured value is higher than the actual value. This indicates an overestimation of the measurement or calculation.

What is a negative percentage error?

A negative percentage error means that the measured value is lower than the actual value. This indicates an underestimation of the measurement or calculation.

Why is percentage error important in science?

Percentage error allows scientists to evaluate the accuracy and reliability of their data. It helps identify any potential sources of error in measurements or calculations, and can guide improvements in experimental techniques.

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