strata combined (n = 120).
This global approach (ignoring strata) in
logarithmic scale seems appropriate here, but since 145 data are now
available, and for this paper to be self-contained, we redo the analysis.
The overall correlation between log(Pu) and log(FIDLER) from 145 pairs is
p = 0.93.
The regression equation is (see Figure 5)
log(Pu) = 1.287 log(FIDLER) + 0.096
,
(2)
(Pu in uCi/m*, FIDLER in 103 cpm).
It is interesting to comment on the
fact that the slope 4 = 1.287 is greater than 1.
Indeed, if the gamma
Tay count recorded by the FIDLER is proportional to the Am concentration
in a sample, and if the ratio R = Pu/Am is approximately constant, then
FIDLER counts are proportional to Pu concentrations and the slope should
be 1.
The larger value found is explained by the difference in support
between a soil sample analyzed for Pu--a 10~gram aliquot from the »v 700
grams of soil collected within the 5~inch-diameter sampling ring--and
the much larger area integrated by a FIDLER reading.
If the measurement
errors effect is not overwhelming, it is to be expected that o2 << OF
and since p is near 1, the regression slope 4 = Pd,/ Oo, is greater than 1.
Further evidence of this interpretation is found using the data of
Lines 1 and 2.
The variances of log FIDLER counts are:
LINE 1
(60 readings)
Contact readings
LINE 2
(25 readings)
0.100
Aboveground readings
0.342
0.087
0.062
As the area integrated by aboveground measurements is larger than the
surface ones, these results are in the right direction, i.e., the variance
of the aboveground readings is smaller than for the surface readings.
The residual variance of the regression is 0.1313.
We will not attempt
to devise confidence intervals for the regression coefficients, for we
. believe that the basic assumptions of independence on which classical
regression theory is built are violated here.
Looking carefully at the plot in Figure 5, one can distinguish two
populations:
one for which FIDLER > 5,000, and the other for which
FIDLER < 5,000.
Doing separate studies for these two subgroups, it is
found that
a
1.
For FIDLER > 5,000, p = 0.89 and the regression is
log(Pu) = 1.293 log (FIDLER) + 0.092
,
(96 pairs) which is practically the same as that derived from the
pooled samples.
This circumstance is reassuring, as it is important
to have a good regression where the activity is high.
It is also
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