### R evaluation of Measurement uncertainty

At the recent Eurachem/PUC ISO 17025 training course in Nicosia, Cyprus on 20-21 February 2020, I had learnt something new from Dr Stephen Ellison’s presentation.

There is a measurement uncertainty package in the R Language, named “**metRology**”. You can download this library when you are in the R environment.

For example, if we were asked to evaluate the uncertainty of the following expression:

expr = A + 2xB + 3xC + D/2

where A = 1, B = 3, C=2, D=11. The sensitive coefficients, c’s, from the above expression are thus 1, 2, 3 and ½ for A, B, C and D, respectively.

Assuming the standard uncertainties of these parameters are
constant at 1/10^{th} of their values, the following steps demonstrate
how the combined standard uncertainty can be evaluated.

*> library(“metRology”)*

Attaching package: ‘metRology’

The following objects are masked from ‘package:base’:

cbind, rbind

*> expr<-expression(A+B*2+C*3+D*/2)

*> x=list(A=1,B=3,C=2,D=11)*

> *u=lapply(x,function(x) x/10)*

*> u*

$A

[1] 0.1

$B

[1] 0.3

$C

[1] 0.2

$D

[1] 1.1

>

>* u.expr<-uncert(expr,x,u,method=”NUM”)*

>* u.expr*

Uncertainty evaluation

Call:

uncert.expression(obj = expr, x = x, u = u, method = “NUM”)

Expression: a + b * 2 + C * 3 + D/2

Evaluation method: NUM

Uncertainty budget:

x u c u.c

A 1 0.1 1.0 0.10

B 3 0.3 2.0 0.60

C 2 0.2 3.0 0.60

D 11 1.1 0.5 0.55

y: 18.5

u(y): 1.01612

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