Spreadsheet method for uncertainty calculation

E.2 Spreadsheet method for uncertainty calculation

f (p+u(p), q ,r..) (denoted by f (p’, q, r, ..) in simplify the calculations shown in Section 8. The

E.2.1 Spreadsheet software can be used to

Figures E2.2 and E2.3), cell C8 becomes procedure takes advantage of an approximate

f (p, q+u(q), r,..) etc.

numerical method of differentiation, and requires

iii) In row 9 enter row 8 minus A8 (for example, knowledge only of the calculation used to derive

cell B9 becomes B8-A8). This gives the values the final result (including any necessary

of u(y,p) as

correction factors or influences) and of the u (y,p)=f (p+u(p), q, r ..) - f (p,q,r ..) etc. numerical values of the parameters and their

uncertainties. The description here follows that of iv) To obtain the standard uncertainty on y, these Kragten [H.12].

individual contributions are squared, added together and then the square root taken, by

E.2.2 In the expression for u(y(x 1 ,x 2 ...x n ))

entering u(y,p) 2 in row 10 (Figure E2.3) and

2 putting the square root of their sum in A10.  ∂ y

∑ That is, cell A10 is set to the formula ⋅ + ⋅

SQRT(SUM(B10+C10+D10+E10))

which gives the standard uncertainty on y. u (x i ) is small compared to x i , the partial

provided that either y(x 1 ,x 2 ...x n ) is linear in x i or

E.2.5 The contents of the cells B10, C10 etc. differentials ( ∂ y / ∂ x i ) can be approximated by:

i ) =(c i u (x i )) ∂ y y ( x i + u ( x i )) − y ( x i )

2 show the squared contributions u(y,x 2

≈ of the individual uncertainty components to the ∂ x i

uncertainty on y and hence it is easy to see which components are significant.

Multiplying by u(x i ) to obtain the uncertainty u (y,x i ) in y due to the uncertainty in x i gives

E.2.6 It is straightforward to allow updated u (y,x i ) ≈ y (x 1 ,x 2 ,.. (x i +u

calculations as individual parameter values

,x ,..x ..x

(x i ))..x n )-y(x 1 2 i n )

change or uncertainties are refined. In step i) Thus u(y,x i ) is just the difference between the

above, rather than copying column A directly to values of y calculated for [x i +u(x i )] and x i

columns B-E, copy the values p to s by reference, respectively.

that is, cells B3 to E3 all reference A3, B4 to E4

E.2.3 The assumption of linearity or small values reference A4 etc. The horizontal arrows in Figure of u(x i )/x i will not be closely met in all cases.

E2.1 show the referencing for row 3. Note that Nonetheless, the method does provide acceptable

cells B8 to E8 should still reference the values in columns B to E respectively, as shown for column

accuracy for practical purposes when considered

B by the vertical arrows in Figure E2.1. In step ii) against the necessary approximations made in above, add the references to row 1 by reference estimating the values of u(x i ). Reference H.12 (as shown by the arrows in Figure E2.1). For discusses the point more fully and suggests

methods of checking the validity of the example, cell B3 becomes A3+B1, cell C4 assumption.

becomes A4+C1 etc. Changes to either parameters or uncertainties will then be reflected

E.2.4 The basic spreadsheet is set up as follows, immediately in the overall result at A8 and the assuming that the result y is a function of the four

combined standard uncertainty at A10. parameters p, q, r, and s:

E.2.7 If any of the variables are correlated, the

i) Enter the values of p, q, etc. and the formula necessary additional term is added to the SUM in for calculating y in column A of the

A10. For example, if p and q are correlated, with spreadsheet. Copy column A across the

a correlation coefficient r(p,q), then the extra term following columns once for every variable in y

2 × r (p,q) × u (y,p) × u (y,q) is added to the calculated (see Figure E2.1). It is convenient to place the sum before taking the square root. Correlation can values of the uncertainties u(p), u(q) and so on therefore easily be included by adding suitable in row 1 as shown. extra terms to the spreadsheet.

ii) Add u(p) to p in cell B3, u(q) to q in cell C4 etc ., as in Figure E2.2. On recalculating the spreadsheet, cell B8 then becomes

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Quantifying Uncertainty Appendix E – Statistical Procedures

Figure E2.1

1 u(p)

8 y=f(p,q,..) y=f(p,q,..) y=f(p,q,..) y=f(p,q,..) y=f(p,q,..)

Figure E2.2

1 u(p)

p+u(p)

q+u(q)

r+u(r)

s+u(s)

8 y=f(p,q,..) y=f(p’,...)

y=f(..q’,..) y=f(..r’,..) y=f(..s’,..)

9 u(y,p)

u(y,q)

u(y,r)

u(y,s)

Figure E2.3

1 u(p)

p+u(p)

q+u(q)

r+u(r)

s+u(s)

8 y=f(p,q,..) y=f(p’,...)

y=f(..q’,..) y=f(..r’,..) y=f(..s’,..)

9 u(y,p)

u(y,q)

u(y,r)

u(y,s)

2 2 2 10 2 u(y) u(y,p) u(y,q) u(y,r) u(y,s)

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Quantifying Uncertainty Appendix E – Statistical Procedures