Stigler (1997, 1999) recounts the history of one of the oldest continuous schemes of sampling inspection carried out by the Royal Mint in London for about eight centuries. The Trial of the Pyx was the final, ceremonial stage in a process designed to ensure that the weight and quality of gold and silver coins from the mint met the standards for coinage.
At regular intervals, coins would be taken from production and deposited into a box called the Pyx. When a Trial of the Pyx was called, the contents of the Pyx would be counted, weighed and assayed for content, and the results would be compared with the standard set for the Royal Mint.
The data frame Pyx
gives the results for the year 1848 (Great Britain, 1848) in which 10,000
gold sovereigns were assayed. The coins in each bag were classified according to the
deviation from the standard content of gold for each coin, called the Remedy,
R = 123 * (12/5760) = .25625, in grains, for a single sovereign.
data(Pyx)
A frequency data frame with 72 observations on the following 4 variables giving the
distribution of 10,000 soverigns, classified according to the Bags
in which
they were collected and the Deviation
from the standard weight.
Bags
an ordered factor with levels 1 and 2
< 3
< 4
< 5
< 6
< 7
< 8
< 9
< 10
Group
an ordered factor with levels below std
< near std
< above std
Deviation
an ordered factor with levels Below -R
< (-R to -.2)
< (-.2 to -.l)
< (-.1 to 0)
< (0 to .l)
< (.1 to .2)
< (.2 to R)
< Above R
count
number of soverigns
Bags
1-4 were selected as "near to standard", bags 5-7 as below standard, bags 8-10 as above standard.
This classification is reflected in Group
.
Great Britain (1848). "Report of the Commissioners Appointed to Inquire into the Constitution, Management and Expense of the Royal Mint." In Vol 28 of House Documents for 1849.
Stigler, S. M. (1997). Eight Centuries of Sampling Inspection: The Trial of the Pyx Journal of the American Statistical Association, 72(359), 493-500
# NOT RUN {
data(Pyx)
# display as table
xtabs(count ~ Bags+Deviation, data=Pyx)
# }
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