很多情况下,被测量Z 不能直接测得,而是由N 个其他量x_1,x_2,\dots,x_n通过函数关系来确定,在统计学上,由于变量含有误差,而使由函数计算出的被测量Z 受其影响也含有误差,(例如,仪器精准度),称之为误差传播。阐述这种关系的定律称为误差传播定律。
误差传播定律
设有一般函数(线性函数和非线性函数)
Z=f(x_1,x_2,\dots,x_n)
式中x_1,x_2,\dots,x_n 为可直接观测的相互独立的未知量,z为不便于直接观测的未知量。已知x_1,x_2,\dots,x_n 的標準差分别为m_1,m_2,\dots,m_n ,现在要求z的標準差m_z 。已知函数z的中误差关系式为m_z^2 =k_1^2 m_1^2+k_2^2 m_2^2+\dots+ k_n^2 m_n^2(其中k_1,k_2,\dots,k_n为任意常数)。由数学分析可知,变量的误差与函数的误差之间的关系,可以近似的用函数的全微分来表达,为此对上式求全微分,并以真误差的符号“Δ”替代微分的符号“d”得
\Delta z=\frac{\partial f}{\partial x_1} \cdot \Delta x_1+\frac{\partial f}{\partial x_2}\cdot \Delta x_2+\cdots+\frac{\partial f}{\partial x_n}\cdot \Delta x_n
式中\frac{\partial f}{\partial x_i} (i=1,2,,…,n)是函数对各个变量变量所取得偏导数,对上式以標準差平方代替真误差,由函数z的中误差关系式可得
m_z^2 = \left(\frac{\partial f}{\partial x_1} \right)^2 m_1^2+\left(\frac{\partial f}{\partial x_2} \right)^2 m_2^2+\dots+ \left(\frac{\partial f}{\partial x_n} \right)^2 m_n^2
将上式取平方根可得误差传播定律的一般形式
m_z=±\sqrt{\left(\frac{\partial f}{\partial x_1} \right)^2 m_1^2+\left(\frac{\partial f}{\partial x_2} \right)^2 m_2^2+\dots+ \left(\frac{\partial f}{\partial x_n} \right)^2 m_n^2}
参见
- 测量精度
- 自動微分
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- 精度衰减因子
- 误差
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- 测量不确定度
- 数值稳定性
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外部链接
- [https://web.archive.org/web/20080516202656/http://physicslabs.phys.cwru.edu/MECH/Manual/Appendix_V_Error%20Prop.pdf Uncertainties and Error Propagation], Appendix V from the [https://web.archive.org/web/20090917235018/http://physicslabs.phys.cwru.edu/MECH/Manual/manual.htm Mechanics Lab Manual], Case Western Reserve University.
- [http://www.incertitudes.fr/book.pdf Mathieu Rouaud, 2013: Probability, Statistics and Estimation] Propagation of Uncertainties in Experimental Measurement.
- [http://www.av8n.com/physics/uncertainty.htm A detailed discussion of measurements and the propagation of uncertainty] explaining the benefits of using error propagation formulas and monte carlo simulations instead of simple significance arithmetic.
- [https://web.archive.org/web/20090307022925/http://www.rit.edu/cos/uphysics/uncertainties/Uncertainties.html Uncertainties and Error Propagation], Vern Lindberg's Guide to Uncertainties and Error Propagation.
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