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Equation 4 · Part 13 · How Scientific Instruments and Metrology Actually Work

addition

uc2(y)=∑i=1N(∂f∂xi)2u2(xi)  +  2∑i=1N−1∑j=i+1N∂f∂xi∂f∂xj u(xi,xj)u_c^2(y) = \sum_{i=1}^{N} \left(\frac{\partial f}{\partial x_i}\right)^2 u^2(x_i) \;+\; 2\sum_{i=1}^{N-1}\sum_{j=i+1}^{N} \frac{\partial f}{\partial x_i}\frac{\partial f}{\partial x_j}\, u(x_i, x_j)
addition

What this part means

Add the term after the plus sign to the term or group before it.

Its job in the formula

Add the term after the plus sign to the term or group before it.

The passage around this formula

The GUM’s central move is to treat every measured or estimated quantity a result depends on as a random variable with its own estimated standard uncertainty, and then to propagate those uncertainties through the mathematical relationship that produces the final result. If a measurement result y is a function of N input quantities, y = f(x1x_1, x2x_2, …\ldots, xNx_N) , the combined standard uncertainty is obtained from a first-order Taylor expansion of that function: uc2(y)=∑i=1N(∂f∂xi)2u2(xi)  +  2∑i=1N−1∑j=i+1N∂f∂xi∂f∂xj u(xi,xj)u_c^2(y) = \sum_{i=1}^{N} \left(\frac{\partial f}{\partial x_i}\right)^2 u^2(x_i) \;+\; 2\sum_{i=1}^{N-1}\sum_{j=i+1}^{N} \frac{\partial f}{\partial x_i}\frac{\partial f}{\partial x_j}\, u(x_i, x_j). The first sum is the familiar root-sum-of-squares combination of independent contributions, each weighted by how sensitive the final result is to that input (the partial derivative, or “sensitivity coefficient”).…

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Learn the underlying idea

Addition combines quantities; subtraction measures the signed difference between them. Parentheses show what is combined before the rest of the expression is evaluated.

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Sources cited in the surrounding passage

These citations provide research context; check each source for the exact claim it supports.