[furanosa2000]

@curiouscat: thats should be the forcing to zero things.. but how to decide that the "b" can be omitted? if there is a "b" value it tells you that the instument is giving you signal, eventhough in the absence of the analyte.. If we omit it, thats mean that we neglect the signal that actually exist.. am I wrong here?

[curiouscat]

@curiouscat: thats should be the forcing to zero things.. but how to decide that the "b" can be omitted? if there is a "b" value it tells you that the instument is giving you signal, eventhough in the absence of the analyte.. If we omit it, thats mean that we neglect the signal that actually exist.. am I wrong here?

The unsaid assumption behind subtracting blanks is that we have a strong prior belief that "Instrument ought to give no signal in absence of concentration. Any signal is mere error."

If yes, then isn't "conc. = a x signal" a better model than "conc. = a x signal + b" (when using corrected signals)

[furanosa2000]

if that the case, I think we have to include the (0,0) point when calculating the linear regression.. discarding the (0,0) will spoil your assumption that "Instrument ought to give no signal in absence of concentration. Any signal is mere error." because when you have this assumption, then (0,0) means no signal when no analyte.. But, if I not mistaken, to discard the "b" value, we have to have some statistical test before we decide it.. anyone familiar with that?

[Borek]

The unsaid assumption behind subtracting blanks is that we have a strong prior belief that "Instrument ought to give no signal in absence of concentration. Any signal is mere error."

No, the assumption is that any signal in the absence of a substance is a background that will not change when the substance is present.

Such a signal can be unavoidable in some systems (say you are measuring presence of a brown contaminant in a slightly yellow substance), and to some extent it is always present - there is no such thing as perfectly transparent cuvette and perfectly transparent solvent (even if we often assume they are perfectly transparent, and we are usually right with a very high accuracy).

[curiouscat]

The unsaid assumption behind subtracting blanks is that we have a strong prior belief that "Instrument ought to give no signal in absence of concentration. Any signal is mere error."

No, the assumption is that any signal in the absence of a substance is a background that will not change when the substance is present.

Such a signal can be unavoidable in some systems (say you are measuring presence of a brown contaminant in a slightly yellow substance), and to some extent it is always present - there is no such thing as perfectly transparent cuvette and perfectly transparent solvent (even if we often assume they are perfectly transparent, and we are usually right with a very high accuracy).

Yes, you said it better.Even so, isn't that a stronger case to use y=ax in the regression?

[JGK]

Actually, shouldn't the best way be to use blank corrected values, discard (0,0) and then use a regression y=ax instead of y=ax+b?

Why is that not an option?

Have you ever tried to blank correct HPLC chromatograms?

[curiouscat]

Actually, shouldn't the best way be to use blank corrected values, discard (0,0) and then use a regression y=ax instead of y=ax+b?

Why is that not an option?

Have you ever tried to blank correct HPLC chromatograms?

Nope.