Combining Errors for Stress Calculation

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The discussion focuses on calculating the standard error for a stress-related calculation involving multiple variables A, B, and C, along with their respective standard errors. The user presents their equations for combining errors and seeks validation on their approach, specifically regarding the use of square root formulas for error propagation. There is confusion about whether the suggested method aligns with standard error calculations or represents a mean square error instead. The user requests clarification on the correctness of their calculations and the appropriate method for determining the standard error. The conversation highlights the complexities of error propagation in statistical calculations.
charlesltl
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Hello Everyone,

I am trying to compute the standard error of a stress related calculation.

Let's consider the following:

A \pm \DeltaA
B \pm \DeltaB

where A and B are the mean values while \DeltaA and \DeltaB are the respective standard errors.

The common combination of errors formulas are as follows:

y = A + B then, \Deltay = √(\DeltaA2+\DeltaB2)

y = k. A then, \Deltay = k.\DeltaA

Now my equation is,

y = k2 . [ A + k1 . ( A + B + C ) ]

May I know if my following working is correct?

( A + B + C )
= √(\DeltaA2+\DeltaB2 + \DeltaC2)

k1 . ( A + B + C )
= k1 . √(\DeltaA2+\DeltaB2 + \DeltaC2)

A + k1 . ( A + B + C )
= √[\DeltaA2 + (k1 . √(\DeltaA2+\DeltaB2 + \DeltaC2))2]
= √[\DeltaA2 + k12 . (\DeltaA2+\DeltaB2 + \DeltaC2)]

k2 . [ A + k1 . ( A + B + C ) ]
= k2 . √[\DeltaA2 + k12 . (\DeltaA2+\DeltaB2 + \DeltaC2)]


I am confused because I was suggested that it should be,
k2 . [ A + k1 . ( A + B + C ) ]
= k2 . √ [k1. \DeltaA2 + k12 . (\DeltaA2+\DeltaB2 + \DeltaC2)]

Your input in highly appreciated.

Charles
 
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That last appears to be the "mean square error" rather than the "error".
 
Would you suggest that my working to compute the standard error is correct?
 
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