Error propagation and significant digits

In summary, when calculating the area of a shape using measured values, it is important to consider the error propagation formula in order to properly estimate the uncertainty of the final answer. In this case, the most accurate answer would be 161.3 ± 2.3 cm, taking into account the error range of the measured values. However, the use of significant figures can also be a helpful tool in determining the appropriate level of precision to show in the final answer.
  • #1
Bolin
2
0
Moderator's note: Thread moved to homework section. Thus no template.

I have an exercise in which I have to calculate the Area from the following measurements:
L = 22.1 ± 0.1 cm
W = 7.3 ± 0.1 cm

Of course, A = W * L = 161.33 but since I have a measurement with just 2 significant digits the results is limited to 2,
A = 160 (or 1.6 x 102 cm).

Now I apply error propagation:
A)2=(σW)2(∂A/∂W)2+(σL)2(∂A/∂L)2
computing the terms, it gives σA = 2.327 cm

Now I write my answer:
160 ± 2 cm

My question is, can I have a error in a decimal place with no significant digits in that decimal place in my answer?
Should it be
161 ± 2 cm?
 
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  • #2
It should be 161 ± 2 cm, sure. The 1 is not "significant" (you are not sure about it), but it is the best estimate, and you certainly know that 161 is a much better estimate than 164.9 or 155.

Significant figures are a bad hand-waving way to estimate uncertainties, error propagation is a much better tool.
 
  • #3
With regard to the number of digits in the principal answer, since you will be specifying an error range you can show as many as you like. The usual limit is because when you do not specify a range the number of digits you show implies the level of accuracy.
Indeed, consider that your final answer has a top end of 160+2 = 162, whereas your more detailed calculation says it could easily reach 163.

As for the error range calculation, I'm sure you have followed what you were taught, but I would like to point out an issue with it. In many experiments, a source of error is from reading off a scale. The error distribution is uniform, +/- half the granularity of the scale markings. The error propagation formula you quote assumes the input error ranges represent some unstated but consistent number of standard deviations, and churns out the corresponding number of standard deviations for the answer. But the product or sum of two uniformly distributed random variables will not have a uniform distribution, so applying the formula will not represent the same number of deviations.

Finally, does it make sense to round down the 2.327? At the least, I would figure out the upper and lower limits based on the unrounded numbers, giving 161.33-2.327=159, and 161.33+2.327=163.66. To encompass that, take the midpoint etc.: 161.3+/-2.3. But that's just what makes sense to me. What you have been taught may be different. If you insist on showing fewer digits, it becomes, say, 161+/-4 in order to encompass the true range, which seems silly.
 
  • #4
Thank you, mfb and haruspex.

I'll keep my answer 161.3 ± 2.3 cm. My confusion originated with the two rules about significant digits: rest/sum and division/multiply. I was using this exercise to understand this and use it in further problems.
 

Related to Error propagation and significant digits

What is error propagation?

Error propagation is the process of determining the uncertainty or error in a calculated result based on the uncertainties or errors in the measurements or values used in the calculation. It involves propagating or carrying the uncertainties through the mathematical operations used in the calculation to estimate the overall uncertainty in the final result.

How is error propagation different from significant digits?

Error propagation involves calculating the overall uncertainty in a result based on the uncertainties in the values used, while significant digits refer to the number of digits in a measurement or value that are considered to be reliable. Error propagation takes into account the significant digits in the values used, but also considers the mathematical operations used in the calculation.

Why is it important to use the correct number of significant digits in calculations?

Using the correct number of significant digits in calculations is important because it ensures that the result is not over or under-estimated. It also helps to maintain the accuracy and precision of the calculated result. Using too many or too few significant digits can lead to an incorrect or misleading result.

How is error propagation used in scientific research?

Error propagation is an important tool in scientific research as it allows for the estimation of uncertainty in calculated results. This is especially useful in experiments or studies where precise measurements are crucial. It helps researchers to evaluate the reliability of their results and determine the impact of uncertainties on their findings.

Are there any limitations to error propagation?

Yes, there are some limitations to error propagation. It assumes that the uncertainties in the measured values are independent and normally distributed, which may not always be the case. Additionally, it only takes into account the uncertainties in the values used and does not consider any potential systematic errors in the measurement process.

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