I Calculating a standard deviation involving weighted samples

  • Thread starter Buzz Bloom
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Buzz Bloom

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I used a spreadsheet (PNG image in main body section) to analyze 12 values with +/- error ranges which I assume for the purpose of this calculation to be standard deviation values. I am seeking conformation or corrections regarding the validity of the method I used.
Below is the spreadsheet image.

The source of the data in the two columns, Ho and +/-, is the following article
Let AHo be the conjoined weighted average values for Ho and the corresponding error ranges.
[1] AHo = AH +/- AE = 67.65 +/- 0.22.​

The Ho column contains the 12 values, Hi, for the Ho variable, i being the index (of a variable value) ranging from 1 to 12.

The +/- column contains for each Hi value the corresponding value of an error range, Ei, which I assume to be of 1 standard deviation σi.

The Source column specifies where in the article the particular 12 values for Hi and Ei are found.

The Wt=... column contains values, Wi, for the weights for calculating weighted sums. I assume that the appropriate choice of weight are the squares of the reciprocals of the Ei values.
[2] Wi = 1/Ei2
The sum of this column is
[3] ΣW = Σ[i=1 to 12] Wi = 25.8982 .​

The Wt*Ho column contains weighted Ho values
[4] WHi = Wi Hi.​
The sum of this column is
[5] ΣWH = Σ[i=1 to 12] WHi = 1751.9631 .​
The weighted average, AH, is
[6] AH = ΣWH / ΣW = 67.65.​

I feel confident that this result is OK for AH. I am less confident that my calculation below of AE is OK. I will present my analysis, and explain my main concern about AE, in what follows.

The D2^2=... column contains values, D2i, of the squares of the 12 differences between AH and a value of Ho.
[7] D2i = (Ho-Hi)2
Althought not part of the calculations, it will later be useful to also have defined the sum of the differences squared.
[8] ΣD2 = Σ[i=1 to 12] (D2i)​

The Wt*D2 column contains values, WD2i, of the product of a weight and a squared difference.​
[9] WD2i = Wi D2i
[10] ΣWD2 = Σ[i=1 to 12] (WD2i) = 1.2992​

I now define Aσ as square root of a quotient: the weighted sum of squared differences and the sum of weights. Using [3] and [10]
[11] Aσ = (WD2/ΣW)1/2 = 1.2992/25.8982 = 0.22​
The main reason I am uncertain is that if all of the Ei values were the same, say 1/s, then then the sum of the weights, ΣW, would be
[12] ΣW = (12/s)2.​
Then the sum of the weighted squares of differences, ΣWD, would be
[`13] ΣWD2 = (1/s2) Σ[i=1 to 12] (D2i)​
= (1/s)2)ΣD2​
and Aσ would be
[14] Aσ = [(1/12)ΣD2]1/21/2.​
Ordinarily, since there are 12 samples I would expect
[15] Aσ = [(1/11) ΣD2]1/21/2.​
Equation [15] is based on the article

I do not know how to adjust this for weighted samples.

Another minor concern is that my assumtion to use 1/Ei2 as weights may not be the right approach. However, I think I have a good rational for doing this, but it is rather complicated, so I will not include it in this post. If anyone would like to see this rationale, I will post it later.
Last edited:


Science Advisor
You can directly calculate the second moments using the weights. Then use the usual formula for the variance as an expression involving the first two moments.

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