Quantitative chromatography results in data which are based on repetitions. Only repetitions provide values about the quality of quantitative data . >>> with one exception, which we only found in 2007  2009 <<< click here.
One can find for all data a quality number: A mean X is the first possible quality number of a series of N repeated measurements: x1, x2, x3, ...xN. The repeatability standard deviation “s” is the quality number for the mean X. Up to now there is no quality number known for the repeatability standard deviation besides this one: the “sf4” value  see under “sf4”. Here is a most simple example to make these statements understandable. Let us assume, two laboratories measured with differing methods four times a special value  let say the concentration of ethanol in wine by strict consecutive repetition: Lab1 found : x1=10.9 vol%; x2=11.2 vol%; x3=10.2 vol%; x4= 10.6 vol% ethanol in a wine sample; Lab2 found : x1=10.709 vol%; x2=10.72 vol%; x3=10.73 vol%; x4= 10.74 vol%
Now how good are the methods  instruments  procedures used in Lab 1 versus Lab 2 although both found the same result “ethanol in (a special) wine” ? This is easily seen by the “sf4” method. In addition the “sf4” procedure will find out if there are systematic errors in the procedure, or the used instrument or just because of the way the samples have been taken. One needs however more than N=4 repetitions as a minimum of analytical effort to be invested. The minimum is N=7, optimal for the “sf4” determination is N=20. If the analytical procedures work fast, there is no problem to use N=20 repetitions and let calculate 203 = 17 “sf4” values. By the way: Lab 2 above did not its best. They have an excellent instrument, but there is a serious sampling problem and if they would solve it, a triple measurement would be MUCH better than a slow, semi precise but regulated and certified (expensive) official method. Can you see it in the given data ? Probably not. But with the help of the “sf4” procedure one can see it clearly.
The worst situation in quantitative analysis is “NO any repetition” which as a critical result means: “nothing is known about the quality of the analytical result”. The optimal situation are results based on N = four repetitions. Why this is true will be shown later.
The structure of a final quantitative analytical result MUST be given in the standard format X, + s, N and this is optimal for N = 4
NOTE: there are other critical data aspects: RUNAWAYS may exist but must be excluded from all quality management with quantitative data. And in case the qualitative data are wrong, all is wrong, because if “FRU” is not “FRU” but “FRA ”we better forget any corresponding quantity result about the substance “FRU”. THIS type of error is chromatography related and unfortunately widely distributed still in the year 100 since the invention of chromatography.
And: Chromatography is everywhere. It may TAKE away substances even completely or enter substances into a sample which never existed therein. Both will for sure falsify the analytical result.
Chromatography acts already in the moment samples are taken, although they have not yet seen any chromatograph. Chromatography happens on any solid or liquid surface. This “environmental or natural everywhere chromatography” can alter drastically an otherwise correctly taken sample or product flow. Thus the “natural everywhere” chromatography is often the source of systematic errors in analytical qualitative as well as quantitative chromatography.
