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Also shown in Figure 2 is a g-PDF curve (red dashed line) for the biased values of T that were used in the previous discussion of bias. Thus the mean of the biased-T g-PDF is at 9.800 − 0.266 m/s 2 (see Table 1). Consider again, as was done in the bias discussion above, a function
0.00034 has 2 significant figures (3 and 4) if the resolution is 0.00001. Zeros to the right of the last non-zero digit (trailing zeros) in a number with the decimal point are significant if they are within the measurement or reporting resolution. 1.200 has four significant figures (1, 2, 0, and 0) if they are allowed by the measurement resolution.
Probability bounds analysis gives the same answer as interval analysis does when only range information is available. It also gives the same answers as Monte Carlo simulation does when information is abundant enough to precisely specify input distributions and their dependencies. Thus, it is a generalization of both interval analysis and ...
Confidence and prediction bands are often used as part of the graphical presentation of results of a regression analysis. Confidence bands are closely related to confidence intervals, which represent the uncertainty in an estimate of a single numerical value. "As confidence intervals, by construction, only refer to a single point, they are ...
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Quantification of Margins and Uncertainty (QMU) is a decision support methodology for complex technical decisions. QMU focuses on the identification, characterization, and analysis of performance thresholds and their associated margins for engineering systems that are evaluated under conditions of uncertainty, particularly when portions of those results are generated using computational ...
The individual measurement uncertainty factors are summarised, usually in tabular form, in the measurement uncertainty budget. Following the description of the measurement procedure and the laying down of the complete model equation, the knowledge of all input variables (values, distribution function , standard uncertainties ) can be ...
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...