By L. Kirkup, R. B. Frenkel
Size shapes clinical theories, characterises advancements in production strategies and promotes effective trade. In live performance with size is uncertainty, and scholars in technology and engineering have to establish and quantify uncertainties within the measurements they make. This ebook introduces dimension and uncertainty to moment and 3rd 12 months scholars of technology and engineering. Its strategy depends on the across the world regarded and prompt guidance for calculating and expressing uncertainty (known through the acronym GUM). The statistics underpinning the tools are thought of and labored examples and routines are unfold during the textual content. unique case reports in accordance with general undergraduate experiments are incorporated to enhance the foundations defined within the ebook. This advisor is additionally valuable to execs in who're anticipated to grasp the modern equipment during this more and more very important zone. extra on-line assets can be found to aid the booklet at www.cambridge.org/9780521605793.
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Extra resources for An introduction to uncertainty in measurement using the GUM
This scatter, or ‘dispersion’, creates an uncertainty in the value obtained for the measurand. This lack of total control over the environment, creating random errors, also affects cases where we make intentional changes to the environment. For example, the electrical resistance of a conducting material varies with temperature. To measure its temperature coefﬁcient of resistance, we measure the resistance at intentionally different temperatures. 2). 1. Random errors when measuring the temperature coefﬁcient of a resistor (courtesy of the National Measurement Institute of Australia).
The extremely challenging measurements of the gravitational constant, G, constitute a prime example. 2 summarises measurements (Quinn et al. 68 × 10−11 m3 · kg−1 · s−2 . 2, some of which do not overlap, indicate the difﬁculty of assigning an uncertainty to the measured value of G. Random and systematic errors have contrasting natures. Random errors can be revealed when we repeat the measurement while trying to keep the conditions constant. Systematic errors can be revealed when we vary the conditions, whether 4 5 6 Josephson’s paper with this discovery is cited, and practical voltage standards based on the Josephson effect are described, in the paper by Hamilton et al.
So if we make the measurement ten times, we are likely to get ten 1 We may obtain exactly the same value simply as a result of the limited resolution of the instrument – for example, if a digital instrument displays only two or three digits. 1. 011 values that, although similar, vary by a small amount. When our intention is to obtain a single value for the measurand, we interpret such variations as the effect of errors. The errors ﬂuctuate, otherwise we would see no variation in our values. Errors that ﬂuctuate, because of the variability in our measurements even under what we consider to be the same conditions, are called random errors.
An introduction to uncertainty in measurement using the GUM by L. Kirkup, R. B. Frenkel