Is a Car's Speed of 110km/h Accurate to 3 or 4 Significant Figures?

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The discussion centers on the interpretation of significant figures, particularly regarding the speed of a car given as 110 km/h. Participants agree that the safest assumption for this value is three significant figures, despite some confusion about whether the trailing zero is significant. It is noted that significant figures are a method to convey measurement accuracy, but their application can be ambiguous, especially with values like 110. The conversation highlights the importance of not reporting results with more significant figures than the least precise measurement, as this can misrepresent accuracy. Overall, the consensus emphasizes the need for common sense and careful consideration of significant figures in practical applications.
  • #61
cjl said:
That's not the point. The customer question was hypothetical: if you had customers who wanted a piece of wood, and you made a hundred pieces of wood (for whatever reason), and they measured anywhere from 1542 to 1566 mm, with a mean of 1554, how would you report their length? 1554 +/- 12 seems to be a good way to me, as it accurately represents both the mean and the variance of the length of the wood.

I agree with you but this is not the uncertainty in the measured length of a plank.
I would quote all of the lengths to +/-1mm, (some would argue that this should be +/-0.5mm) I would use a steel tape measure and the smallest divisions are 1mm.
The fact that all of the planks could not be cut to within +/-1mm of each other is a different thing.
 
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  • #62
So you now know why measurements are presented in such a way?

technician said:
I am curious to know what measurements in what experiment resulted in a number to be quoted like this.
 
  • #63
milesyoung said:
So you now know why measurements are presented in such a way?
In that kind of example...of course, there is no problem.
It is like reporting the heights of people in a population (I would even say sig figs are meaningless !)

The original figures related to reporting a measurement, ie the height of a person, (sig figs are not meaningless !) not representing the range of measurements in a sample of 100.

Extra
I have done a quick Google search for 'significant figures'...there is a wealth of information relating the importance of sig figs and the links with accuracy.
Nowhere will you be told to ignore them, nowhere will criticism of education systems be used to discredit sig figs.
I think that I will rest my case in those references.
 
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  • #64
technician said:
It is like reporting the heights of people in a population (I would even say sig figs are meaningless !)
In this case you'd probably give the data in the form of a distribution instead. The mean and range of heights isn't very informative unless these parameters happen to uniquely describe the distribution.

technician said:
The original figures related to reporting a measurement, ie the height of a person, (sig figs are not meaningless !) not representing the range of measurements in a sample of 100.
Be it a measurement of height or the length of one of your wood pieces, we're still just specifying a number with some uncertainty.

If you care about your data, you'd apply some method of error analysis when you do calculations with it. You'd most definitely not rely on counting significant figures.

technician said:
I have done a quick Google search for 'significant figures'...there is a wealth of information relating the importance of sig figs and the links with accuracy.
I'd be suprised if "significant figures" and "accuracy" didn't generate a lot of hits.

technician said:
Nowhere will you be told to ignore them, nowhere will criticism of education systems be used to discredit sig figs.
I have the following resource for you from the PHYS-L mailing list of the Buffalo State University in New York. Some background:

PHYS-L is a list dedicated to physics and the teaching of physics with about 700 members from over 35 countries, the majority of whom are physics educators. Traffic varies from zero to sixty messages/day with an average of about ten per day. All postings are archived. Noninflammatory, professional and courteous postings intended to inform members on how to better understand, teach and learn physics are always welcome.

PHYS-L is officially supported by the SUNY-Buffalo State College Department of Physics, SUNY-University at Buffalo Department of Physics, and unofficially by the American Association of Physics Teachers (AAPT).

The resource was compiled by John S. Denker, formerly of Bell Labs, from the PHYS-L archives. Here's a quote from it:
Executive summary: No matter what you are trying to do, significant figures are the wrong way to do it.

Measurements and Uncertainties versus Significant Digits or Significant Figures

You can find plenty more in the public domain on error analysis.

technician said:
I think that I will rest my case in those references.
You didn't provide any.
 
  • #65
I could not resist looking at this reference. 99.9%(+/-0.1%) of this is concerned with analysing data extracted from a distribution NOT with uncertainty in making a measurement. Like my planks, the spread in 100 planks may be +/-12mm but the uncertainty in anyone plank is +/-1mm...different things.
It is full of contradiction and confusion apparently 1.8 is the same as 1.80...it is not in the world of measurement ! 'hogwash' to use the author's vernacular.

Below is one of his lists of evidence, I have highlighted in red evidence that would be called 'anecdotal', ie no evidence of any worth.
I have highlighted in blue statements that make sense.

The disadvantages of sig figs include:

Given something that is properly expressed in the form A±B, such as 1.234±0.055, converting it to sig figs gives you an excessively crude and erratic representation of the uncertainty, B. See section 7.5.3 and especially section 15.5.
Sig figs also cause excessive roundoff error in the nominal value, A. This is a big problem. See section 6.8 for a concrete example.
Sig figs cause people to misunderstand the distinction between roundoff error and uncertainty. See section 6.8 and section 5.4.
Sig figs cause people to misunderstand the distinction between uncertainty and significance. See section 13, especially section 13.3.
Sig figs cause people to misunderstand the distinction between the indicated value and the corresponding range of true values. See section 4.6.
Sig figs cause people to misunderstand the distinction between distributions and numbers. Distributions have width, whereas numbers don’t.Uncertainty is necessarily associated with some distribution, not with any particular point that might have been drawn from the distribution. See section 1.2, section 5.4, and reference 1.
As a consequence, this makes people hesitate to write down numbers. They think they need to know the amount of supposedly “associated” uncertainty before they can write the number, when in fact they don’t. Very commonly, there is not any “associated” uncertainty anyway.
Sig figs weaken people’s understanding of the axioms of the decimal numeral system. See section 15.5.7.
Sig figs give people the idea that N nominal values should be associated with N uncertainties, which is just crazy. In fact the number of uncertainties scales like (N2 + N)/2, as discussed in section 8.1.
The sig figs approach cannot possibly apply to algebraic variables such as A±B, so you are going to have to learn the A±B representation anyway. Having learned it, you might as well use it for decimal numerals such as 1.234±0.055. See section 15.5.5.
Et cetera

There are 89 pages in this reference...full of contradiction and condescending, snappy quotes
Thats all for now :wink:
 
  • #66
technician said:
I could not resist looking at this reference. 99.9%(+/-0.1%) of this is concerned with analysing data extracted from a distribution NOT with uncertainty in making a measurement.
I think you have misunderstood what you've read. Yes, the resource is in large part based on statistical methods, but that's not really suprising, given the subject.

technician said:
Like my planks, the spread in 100 planks may be +/-12mm but the uncertainty in anyone plank is +/-1mm...different things.
If the uncertainty was +/- 1 mm, how could you ever produce a piece with a length of 1542 mm?

technician said:
Below is one of his lists of evidence, I have highlighted in red evidence that would be called 'anecdotal', ie no evidence of any worth.
You've highlighted portions of a summary, the "evidence" is given in the sections that are linked to.


I'd be inclined to ask you for examples of what you disagree with, but your responses in this thread, and others where we have posted, have left me flabbergasted. I have tried to argue what I believe to be true to the best of my ability, but somehow it seems that, regardless of the argument, you discard it just the same, and that's not how I wish to spend my time on this forum.
 
  • #67
If the uncertainty was +/- 1 mm, how could you ever produce a piece with a length of 1542 mm?
I couldn't !
BUT I could produce a plank that was measured to be 1542 +/-1mm (the 2 at the end let's you know that the measurement was made with a mm scale)

I'd be inclined to ask you for examples of what you disagree with, but your responses in this thread, and others where we have posted, have left me flabbergasted. I have tried to argue what I believe to be true to the best of my ability, but somehow it seems that, regardless of the argument, you discard it just the same, and that's not how I wish to spend my time on this forum.

couldn't have said it better myself.
I take it this will be the last in this post.

Do you think that 1.8 is the same as 1.80 is the same as 1.800?
 
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  • #68
technician said:
Do you think that 1.8 is the same as 1.80 is the same as 1.800?

They are mathematically equivalent, and they all represent precisely the same number.
 
  • #69
In terms of MEASUREMENT these numbers are not the same. This is the importance of knowing what is meant by significant figures.
!.8 means that the measured quantity lies between 1.7 and 1.9
1.80 means the quantity is between 1.79 and 1.81
and so on
I include a sketch of scales and scale divisions that lead to this logic.
For the number 1.80 the last zero is significant
 

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  • #70
This is getting boring. How do you represent 1.80±0.02?
 
  • #71
This is getting boring. How do you represent 1.80±0.02?
You have done it !
It means you probably used a scale such as this



"If you are bored you are not paying attention"
 

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  • #72
technician said:
This is getting boring. How do you represent 1.80±0.02?
You have done it !

Sigh.

How do you represent 1.80±0.02 using significant figures?
 
  • #73
like this
technician said:
This is getting boring. How do you represent 1.80±0.02?
You have done it !
It means you probably used a scale such as this



"If you are bored you are not paying attention"
 
  • #74
The original question has been answered, and this is getting tedious. This thread is done.

Zz.
 

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