Precision
- Arbitrary-precision arithmetic, methods for computing with big numbers
Precision (march)
Precision is the authorized march of Royal Military College of Canada. The RMC band performs Precision on parades for march pasts, on Ex Cadet Weekends for the parade to the Memorial Arch, and on the return, the Cadet Wing sings Tom Gelley’s words to welcome the Ex Cadets to the Parade Square.
History
Precision was composed in 1932 by Denise Chabot, wife of Major C. A. Chabot, a Royal Canadian Artillery officer on staff as professor of French at the College at the time. She earned the degree of Associate of the Royal Conservatory of Music and was the president of the Kingston Music Club.
Precision was inspired by "Madelon", one of the popular marching songs sung and whistled by the cadets marching on their way to the Riding School, and the favourite song of the Class of 1932. Mme Chabot improvised a variation on the song, to represent the cadence of the cadets on the march. The composition starts, “We are the gentlemen cadets of RMC We have sworn to love and serve Her Majesty…”
Precision (statistics)
In statistics, the dual term variability is preferred to the use of precision. Variability is the amount of imprecision.
There can be differences in usage of the term for particular statistical models but, in common statistical usage, the precision is defined to be the reciprocal of the variance, while the precision matrix is the matrix inverse of the covariance matrix.
One particular use of the precision matrix is in the context of Bayesian analysis of the multivariate normal distribution: for example, Bernardo & Smith prefer to parameterise the multivariate normal distribution in terms of the precision matrix rather than the covariance matrix because of certain simplifications that then arise.
History
The term precision in this sense (“mensura praecisionis observationum”) first appeared in the works of Gauss (1809) “Theoria motus corporum coelestium in sectionibus conicis solem ambientium” (page 212). Gauss’s definition differs from the modern one by a factor of 
. He writes, for the density function of a normal random variable with precision h,
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