Uncertainty and Quality in Science for Policy60 -I 137.0~29 ERROR BARS • tONE (1" \ \ \ 4\0 \ \ E \ a. a. \ Z30 \ 137.0388 \ 0 137.0377 \ ~ \ ~20 \ \ 0 to 0 '50 Fig.1. Successive recommended values of the fine-structure constand IX-I (B. N. Taylor et 01., 1969,7) reminder that the value is not fully accepted by colleagues, since they will expect it to jump about for a while longer. Our next example is taken from a recent study in the social sciences. It shows how a set of related estimates of uncertainty can be expressed clearly and effectively by NUSAP. Suppose that we wish to forecast what the future price of a basic commodity might be, especially when at the moment its price is artificially maintained by a cartel of producers. There is no experimental evidence on such a future contingency, and yet we are not completely in the dark. There is a long history of expertise in the field; and there is a well-tried standard model by which experts' guesses can be translated into mathematical form. |
Contents
III | 7 |
IV | 9 |
V | 11 |
VI | 13 |
VII | 15 |
VIII | 17 |
IX | 18 |
X | 20 |
XLVII | 101 |
XLVIII | 102 |
XLIX | 108 |
L | 110 |
LI | 111 |
LII | 113 |
LIII | 115 |
LIV | 116 |
XI | 21 |
XII | 25 |
XIII | 27 |
XIV | 28 |
XV | 31 |
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XVIII | 39 |
XIX | 40 |
XX | 43 |
XXI | 44 |
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XXV | 49 |
XXVI | 52 |
XXVII | 54 |
XXVIII | 56 |
XXIX | 58 |
XXX | 60 |
XXXI | 65 |
XXXII | 69 |
XXXIII | 71 |
XXXIV | 73 |
XXXV | 76 |
XXXVI | 78 |
XXXVII | 80 |
XXXVIII | 83 |
XXXIX | 85 |
XL | 87 |
XLI | 88 |
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XLIII | 93 |
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XLV | 97 |
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LV | 118 |
LVI | 121 |
LVII | 123 |
LVIII | 124 |
LIX | 126 |
LX | 128 |
LXI | 131 |
LXII | 132 |
LXIII | 133 |
LXIV | 134 |
LXV | 137 |
LXVI | 139 |
LXVII | 143 |
LXVIII | 146 |
LXIX | 149 |
LXX | 151 |
LXXI | 156 |
LXXII | 159 |
LXXIII | 164 |
LXXIV | 165 |
LXXV | 169 |
LXXVI | 172 |
LXXVII | 173 |
LXXVIII | 176 |
LXXIX | 179 |
LXXX | 182 |
LXXXI | 184 |
LXXXII | 188 |
LXXXIII | 192 |
LXXXIV | 195 |
LXXXV | 197 |
LXXXVI | 204 |
LXXXVII | 209 |
LXXXVIII | 211 |
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Common terms and phrases
aggregated ambiguity analysis applied appropriate arithmetic aspects assessment border with ignorance calculated model outputs cognitive concepts conveyed craft skills criteria defined digits effective error estimate evaluation example experts field fine-structure constant formal function Funtowicz indicators inexactness infinite regress inputs involved judgements knowing-how knowledge management of uncertainty maps mathematical means measurement modes notational scheme numbers NUSAP expression NUSAP notational NUSAP representation NUSAP scheme NUSAP system operations parameters particular pedigree matrix Peer-Acceptance phases philosophical physical constants place-value place-value notation policy-related research practice precision Probabilistic Risk Assessment probability distribution problems procedure production propagation of uncertainties quality assurance quantitative information radioactive decay radiological radionuclide Ravetz reflects relation relevant reliability represented Risk Index scale scientific information scientists scores set of weights sexagesimal simple sorts of uncertainty spread standard statistics symbols systematic error technical techniques technologies theory topology traditional unit users Washington D.C.