Ed, no the fact that you don't, can't or won't estimate the precision
doesn't change anything (only as you say it becomes a poorly designed
experiment).  A measurement has a standard deviation regardless of whether
you possess an estimate of its value or not.  The exact true value of the
standard deviation can never be known, just as the true value of any
physical quantity can never be known, even after measuring it umpteen
times!  The measurements are only estimates of the true value, sampled from
the error distribution of the true value.

The experimental estimate of the standard deviation is called the 'standard
uncertainty' (indeed I remember when it was called the 'estimated standard
deviation' or e.s.d.), again sampled from the error distribution of the
SD.  Sometimes I see in the literature the term 'estimated standard
uncertainty' but this is a term that does not appear in any literature on
statistics (it seems to be peculiar to protein crystallography
literature!).  Also it would then be the 'estimated estimated standard
deviation' which is one more level of estimation that you need (an estimate
of an estimate is still an estimate - it just has a bigger uncertainty than
the previous estimate!).

See http://physics.nist.gov/cgi-bin/cuu/Info/Constants/definitions.html for
the terminology approved by NIST.

Cheers

-- Ian


On 13 March 2013 20:36, Ed Pozharski <[email protected]> wrote:

> Ian,
>
> On Wed, 2013-03-13 at 19:46 +0000, Ian Tickle wrote:
> > So I don't see there's a question of wilfully choosing to ignore. or
> > not sampling certain factors: if the experiment is properly calibrated
> > to get the SD estimate you can't ignore it.
> >
>
> So perhaps I can explain better by using the same example of protein
> concentration measurement.  It is certainly true that only taking one
> dilution is "poor design". (Although in crystallization practice it may
> not matter given that it is not imperative to have a protein exactly at
> 10 mg/ml, 9.7 will do).  If I don't bother including pipetting precision
> in my error estimate either by direct experiment or by using
> manufacturer's declaration I am willfully ignoring this source of error.
> That would be wrong.
>
> But what if I only have one measurement worth of sample?  And pipetting
> precision cannot be calibrated (I know it can be so this is hypothetical
> - say pipettor was stolen and company that made it is out of business,
> their offices burned down by raging mob).  Is the pipetting error now
> systematic because experimental situation (not design) prevents it from
> being sampled or estimated?
>
> I actually like the immutable error type better for my own purposes, but
> I am trying to see whether some argument might stand that allows some
> error that can be sampled to be called inaccuracy nonetheless.
>
> Cheers and thanks,
>
> Ed.
>
>
> --
> I don't know why the sacrifice thing didn't work.
> Science behind it seemed so solid.
>                                     Julian, King of Lemurs
>
>

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