On 3 Mar 2004 07:24:00 -0800, [EMAIL PROTECTED] (Euh) wrote:

> "Jim Snow" <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>...
> > "Euh" <[EMAIL PROTECTED]> wrote in message
> > news:[EMAIL PROTECTED]
> > > Hello all,
> > >
> > > I'm trying to evaluate the concentration of suspended particles �n a
> > > flask.
> > > I took 3 differents samples from the flask and, for each sample, I did
> > > 20 counts under the microscope (= at 20 different locations on the
> > > microscope slide)
> > 
> >   (snip)
> > 
> > 
> > > Data (each column is a sample, each row is a count)
> > >
> > > 98 108 115
> > > 123 102 120
> > > 88 90 93
> > > 65 71 92
> > > 95 56 131
> > > 68 145 138
> > > 114 136 116
> > > 82 100 98
> > > 87 85 70
> > > 109 116 56
> > > 134 157 34
> > > 102 60 113
> > > 130 90 125
> > > 53 121 63
> > > 124 111 81
> > > 114 92 117
> > > 118 131 109
> > > 76 55 113
> > > 97 256 108
> > > 79 146 72
> > 
> >     Your counts ,I think, are supposed to be counts of the number of
> > particles in equal volumes of a well mixed suspension. If this were
> > true, the numbers would follow a Poisson distribution, characterised
> > by the population variance being equal to the mean. This is clearly
> > not true for your samples:
> > 
> >   Means are 97.8,  111.4,  98.2   Variances are  527,  2061,  760
> > 
> >   Either the volumes contributing to each count are variable or mixing
> > has not been thorough enough, or I do not understand your description
> > of the data.
> > 
> >  HTH  Jim Snow
> 
> It's not a problem of mixing, but it's related. Particles tend to form
> aggregates which makes it harder to count the total number.
> On top of that, some particles are degraded over time and you end up
> with debris in the solution. Sometimes, it's hard to tell if what you
> see is a small particle (that should be counted) or a debris (should
> be ignored). it's judgment based...hence the huge variation.
> 
> By adding one count at a time and computing a t-value, I've been able
> to evaluate that approx 10 counts are required to get close to the
> true value (15 % error).

I find myself wondering about "stratified sampling"  or
"blind (or mechanical) selection" -- because those 20
values offered are highly inconsistent.  It is not possible
that they represent a single, homogeneous mean, but
they *could*  represent a single "totality"  if they do 
represent strata, in the style of stratified-sampling.

One curiosity in the numbers as they have been described, 
as I see it, is that the 3 samples ended up with averages
so similar.  I think it must be an accident, unless it 
represents an unconscious *bias*  to represent different
amalgams with equal fractions.  

 - I conclude that I want to see an explanation of the 
sampling, before I believe that the results are not 
confounded or biased by 'rater'  effects that could be
sizable.

> 
> 
> I've also computed the number of samples required based on the
> standard deviation of all the counts and this gives me a higher
> number.

-- 
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
 - I need a new job, after March 31.  Openings? -
.
.
=================================================================
Instructions for joining and leaving this list, remarks about the
problem of INAPPROPRIATE MESSAGES, and archives are available at:
.                  http://jse.stat.ncsu.edu/                    .
=================================================================

Reply via email to