The Classical Statistical Presumption of Normally Distributed Experiment Test Program Datum Values

Author(s):  
John J. Friel

Committee E-04 on Metallography of the American Society for Testing and Materials (ASTM) conducted an interlaboratory round robin test program on quantitative energy dispersive spectroscopy (EDS). The test program was designed to produce data on which to base a precision and bias statement for quantitative analysis by EDS. Nine laboratories were sent specimens of two well characterized materials, a type 308 stainless steel, and a complex mechanical alloy from Inco Alloys International, Inconel® MA 6000. The stainless steel was chosen as an example of a straightforward analysis with no special problems. The mechanical alloy was selected because elements were present in a wide range of concentrations; K, L, and M lines were involved; and Ta was severely overlapped with W. The test aimed to establish limits of precision that could be routinely achieved by capable laboratories operating under real world conditions. The participants were first allowed to use their own best procedures, but later were instructed to repeat the analysis using specified conditions: 20 kV accelerating voltage, 200s live time, ∼25% dead time and ∼40° takeoff angle. They were also asked to run a standardless analysis.


1968 ◽  
Vol 78 (2, Pt.1) ◽  
pp. 269-275 ◽  
Author(s):  
Wesley M. DuCharme ◽  
Cameron R. Peterson
Keyword(s):  

1972 ◽  
Vol 28 (03) ◽  
pp. 447-456 ◽  
Author(s):  
E. A Murphy ◽  
M. E Francis ◽  
J. F Mustard

SummaryThe characteristics of experimental error in measurement of platelet radioactivity have been explored by blind replicate determinations on specimens taken on several days on each of three Walker hounds.Analysis suggests that it is not unreasonable to suppose that error for each sample is normally distributed ; and while there is evidence that the variance is heterogeneous, no systematic relationship has been discovered between the mean and the standard deviation of the determinations on individual samples. Thus, since it would be impracticable for investigators to do replicate determinations as a routine, no improvement over simple unweighted least squares estimation on untransformed data suggests itself.


AEI 2019 ◽  
2019 ◽  
Author(s):  
S. Shadravan ◽  
C. Ramseyer
Keyword(s):  

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