A Handy Tool For Convenient Error Propagation Analysis: A User Form For Error Influence Coefficients
Author(s) -
Sheldon Jeter
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--14693
Subject(s) - propagation of uncertainty , uncertainty analysis , measurement uncertainty , computer science , range (aeronautics) , set (abstract data type) , sensitivity analysis , observational error , scrutiny , random error , variation (astronomy) , interval arithmetic , data mining , algorithm , industrial engineering , statistics , mathematics , simulation , engineering , mathematical analysis , physics , law , political science , astrophysics , bounded function , programming language , aerospace engineering
Complete uncertainty analysis in experimental engineering requires two distinct and complementary calculations. Statistical analysis of repeated measurements is needed to compute the Uncertainty A, which is the uncertainty due to random variation. Complementary physical analysis of the measurement system is also needed to evaluate the Uncertainty B or the range in possible bias or built in error. The more interesting and important applications of Uncertainty B analysis are encountered when considering an indirect measurement. An indirect measurement is merely a value calculated from a set of direct measurements. Error Propagation Analysis (EPA) is usually necessary to estimate the Uncertainty B for indirect measurements.
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