Themes > Science > Chemistry > Miscellenous > Help file Index > Error Analysis > Multiplication and Division of Values with Standard Deviation


When you want to multiply or divide average values reported with their standard deviations, you don't simply add the standard deviations to produce the final standard deviation. Instead, you square the fractional standard deviations, add them, then take the square root of the sum to get the fractional total deviation. If you have values A +- dA, B +- dB, ... and want to compute X = A*B*..., the total error dX is then

dX/X = sqrt( (dA/A)2 + (dB/B)2 +...)
Note that you will add the squares of the errors even if you are dividing the actual values.

An example should make this clearer. Assume we have the following three values with their standard deviations

  • A = 1.67 +- 0.05
  • B = 5.23 +- 0.09
  • C= 1.88 +- 0.07
and we want to compute X = A*B/C. The actual problem is trivial:
(1.67 * 5.23)/1.88 = 4.65
To compute the standard deviation of the result, we must sum the squares of the relative errors and then take the sqaure root.
dX/4.65 = sqrt( (0.05/1.67)2 + (0.09/5.23)2 + (0.07/1.88)2)
Stot/4.65 = sqrt(0.000896 + 0.000296 + 0.00139)
Stot/4.65 = 0.0508
Stot = 0.236
Since we only report error to 1 significant figure, the answer to this problem would be 4.7+-0.2

See also the page on handling addition and subtraction with errors. If you are given a problem that has both addition/subtraction and multiplication/division, you should work through the errors in the same order that you do the math: multiplication/division before addition/subtraction. For example, if you had to compute X = A*B + C, work out the error in A*B by the multiplication rule, then work out the error in (A*B) + C by the addition rule.

Example: You want to perform the calculation X = A/(B*C*D). What is the result and the standard deviation of the result?

  • A = 14.99 +- 0.01
  • B = 3.56 +- 0.09
  • C = 10.1 +- 0.5
  • D = 1.000 +- 0.006

Solution: The average result is easy to compute:

14.99/(3.56 * 10.1 * 1.000) = 0.417

The relative error is the square root of the sum of squares of the relative errors

dX/0.417 = sqrt( (0.01/14.99)2 + (0.09/3.56)2 + (0.5/10.1)2 + (0.006/1)2)
dX/0.417 = sqrt(4.45*10-7 + 6.39*10-4 + 2.45*10-3 + 3.60*10-5)
dX/0.417 = sqrt(3.13*10-3)
dX/0.417 = 0.0559
dX = 0.0233
The answer would thus be reported as 0.42 +- 0.02. Note that the vast majority of the error came from one piece of data: 10.1 +- 0.5. It's often the case in experiments that one set of data has a much larger error than the rest. This is known as the limiting error- you may know the temperature and pressure to 8 significant figures, but if you only have the volume to 2 the error in the volume will be the limiting error.


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