RSD is used to compare sets that can't be compared in absolute values. Like comparing an effect of a weight control drug on elephants and mice. Comparing their absolute SD doesn't make sense, so you normalize by their mean value.
Not only.
if you want to compare results of the same analysis with different method / on different systems /different labs etc.
Or your method gives you a default error of 0.1%w/w. Then it depends if you measure an assay >95%w/w or related compounds <1%w/w.
Of course you can always give the error in absolute measures but in relative terms the precision will be much easier to recognize.
You can also look at electronics components e.g. resistors and capacitors, they are usually specified by their relative error, not absolute ones.
This one I don't get.. They have the same accuracy (or better call it precision). What makes you switch to relative units? In the example with elephants & mice I wanted to compare the effect of the drug on one animal vs the other. But in this example why would you want to compare?
yeah maybe a missuse of the two terms..
Both measurements will have the absolute accuracy of 1 mm but their precisions are 10 and 1 ppm.
If you think of it as multiple measurments you will get results of 99.999 - 100.001 m or 999.999 - 10000.001 m.
With those multiple measurements you will get a (Gaussian) distribution with their means and SD.
Here again - why is it relative to the measured mass? When I look at the mass spectra, I'd like to understand whether this particular measured value is my analyte or not. So I'll look how far the value from the theoretical value, and for this it's much easier to use +/- 0.015. I can see these values with my eyes on the chart, while ppm doesn't tell me anything..
Why not?
It may also be a matter of taste how to describe the error. But the relative became more popular, because it expresses the precision of the measurement.
Just like the retention time window for peak recognition. If you know that your flow is stable (precise) and accurate to e.g. 1% then your retention times will also be in that order, so it's easier to define the RT windows as +/-1%. So late eluter will get a broader window than earlier ones.
of course you could also specify it in absolute time, but then later peaks may fall out of the window quite frequently. Or the window is to broad for earlier peaks and missidentification may occur.
To make it concrete, you have 2 analytes A (100Da) and B (1000Da), and the measurements find 101Da and 1001Da. Would you say that A wasn't found, while B might actually be there?
probably yes, depending on the accuracy. If both have an error of 1000 ppm, the A is significantly different but B is not.