Your comment seems to be written by somebody who has no idea what they are talking about. (Meaning, the contents of the article they supposedly just read.)
Once you bother to get past the first paragraph, the entire rest of the article explains exactly why the extra digits are useful to the author in some specific circumstances. (Hint: it has exactly nothing whatsoever to do with propagation of significant digits, which they also clearly demonstrate their understanding of.)
This has everything to do with propagation of significant digits.
Since the data in the mentioned experiment are "exact" measurements without uncertainty, the data is being treated as infinite (or rather, machine) precision, where the percentage difference would also have to be reported at machine precision, which is what the author is getting at:
>> 100 * ((37/45) / (312/401) - 1)
5.676638176638171
However, assume that the same kind of data came from a sensor with some uncertainty (say, 2 digits precision), then you could have, within that uncertainty bound, L = 46 (instead of L = 45, etc.), R = 400 (and still L+R = 446), which would give
>> 100 * ((37/46) / (312/400) - 1)
3.121516164994431
Obviously, this is a huge difference, which is why propagation of significant digits needs to be considered if there is any uncertainty in the data. And in that case adding more digits will not buy you anything.
The author's case is a special case where the values are "exact" and therefore you need more precision in the reported percentage value. But it is often not applicable in science when measured data has uncertainty.
The ratios in the example are on integer numbers of people, not measurements. You seem to get that, so I'm struggling to imagine what "the same kind of data" from a "sensor with some uncertainty" would even mean. Or what the hypothetical experimentalist who wrote your modified version of the equation would even be trying to compute using the measurements, in that case. Or why any reader would be attempting to "reverse engineer" the experimental details in a case like that. It just flat out doesn't apply to the situations the author is writing about. If I'm not getting your point, feel free to paint me a scenario with a bit more specificity.
Anyway, if you're worried about not tracking uncertainty in calculations, well, I can quote from the article:
If your point is that there’s lots of uncertainty, then add a confidence interval or write “±” whatever.
That solves the problem in an equally valid way, no? The author is clearly not some ignoramus who doesn't understand significant digits and needs to take a Physics 101 class.
Comments
Your comment seems to be written by somebody who has no idea what they are talking about. (Meaning, the contents of the article they supposedly just read.)
Once you bother to get past the first paragraph, the entire rest of the article explains exactly why the extra digits are useful to the author in some specific circumstances. (Hint: it has exactly nothing whatsoever to do with propagation of significant digits, which they also clearly demonstrate their understanding of.)
This has everything to do with propagation of significant digits.
Since the data in the mentioned experiment are "exact" measurements without uncertainty, the data is being treated as infinite (or rather, machine) precision, where the percentage difference would also have to be reported at machine precision, which is what the author is getting at:
5.676638176638171
However, assume that the same kind of data came from a sensor with some uncertainty (say, 2 digits precision), then you could have, within that uncertainty bound, L = 46 (instead of L = 45, etc.), R = 400 (and still L+R = 446), which would give
3.121516164994431
Obviously, this is a huge difference, which is why propagation of significant digits needs to be considered if there is any uncertainty in the data. And in that case adding more digits will not buy you anything.
The author's case is a special case where the values are "exact" and therefore you need more precision in the reported percentage value. But it is often not applicable in science when measured data has uncertainty.
The ratios in the example are on integer numbers of people, not measurements. You seem to get that, so I'm struggling to imagine what "the same kind of data" from a "sensor with some uncertainty" would even mean. Or what the hypothetical experimentalist who wrote your modified version of the equation would even be trying to compute using the measurements, in that case. Or why any reader would be attempting to "reverse engineer" the experimental details in a case like that. It just flat out doesn't apply to the situations the author is writing about. If I'm not getting your point, feel free to paint me a scenario with a bit more specificity.
Anyway, if you're worried about not tracking uncertainty in calculations, well, I can quote from the article:
That solves the problem in an equally valid way, no? The author is clearly not some ignoramus who doesn't understand significant digits and needs to take a Physics 101 class.