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Clarify "IID" #58

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Dec 19, 2020
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20 changes: 12 additions & 8 deletions src/Statistics.jl
Original file line number Diff line number Diff line change
Expand Up @@ -306,8 +306,9 @@ end
Compute the sample variance of collection `itr`, with known mean(s) `mean`.

The algorithm returns an estimator of the generative distribution's variance
under the assumption that each entry of `itr` is an IID drawn from that generative
distribution. For arrays, this computation is equivalent to calculating
under the assumption that each entry of `itr` is a sample drawn from the same
unknown distribution, with the samples uncorrelated.
For arrays, this computation is equivalent to calculating
`sum((itr .- mean(itr)).^2) / (length(itr) - 1)`.
If `corrected` is `true`, then the sum is scaled with `n-1`,
whereas the sum is scaled with `n` if `corrected` is
Expand Down Expand Up @@ -343,8 +344,9 @@ end
Compute the sample variance of collection `itr`.

The algorithm returns an estimator of the generative distribution's variance
under the assumption that each entry of `itr` is an IID drawn from that generative
distribution. For arrays, this computation is equivalent to calculating
under the assumption that each entry of `itr` is a sample drawn from the same
unknown distribution, with the samples uncorrelated.
For arrays, this computation is equivalent to calculating
`sum((itr .- mean(itr)).^2) / (length(itr) - 1))`.
If `corrected` is `true`, then the sum is scaled with `n-1`,
whereas the sum is scaled with `n` if `corrected` is
Expand Down Expand Up @@ -418,8 +420,9 @@ stdm(A::AbstractArray, m; corrected::Bool=true) =
Compute the sample standard deviation of collection `itr`.

The algorithm returns an estimator of the generative distribution's standard
deviation under the assumption that each entry of `itr` is an IID drawn from that generative
distribution. For arrays, this computation is equivalent to calculating
deviation under the assumption that each entry of `itr` is a sample drawn from
the same unknown distribution, with the samples uncorrelated.
For arrays, this computation is equivalent to calculating
`sqrt(sum((itr .- mean(itr)).^2) / (length(itr) - 1))`.
If `corrected` is `true`, then the sum is scaled with `n-1`,
whereas the sum is scaled with `n` if `corrected` is
Expand Down Expand Up @@ -461,8 +464,9 @@ std(iterable; corrected::Bool=true, mean=nothing) =
Compute the sample standard deviation of collection `itr`, with known mean(s) `mean`.

The algorithm returns an estimator of the generative distribution's standard
deviation under the assumption that each entry of `itr` is an IID drawn from that generative
distribution. For arrays, this computation is equivalent to calculating
deviation under the assumption that each entry of `itr` is a sample drawn from
the same unknown distribution, with the samples uncorrelated.
For arrays, this computation is equivalent to calculating
`sqrt(sum((itr .- mean(itr)).^2) / (length(itr) - 1))`.
If `corrected` is `true`, then the sum is scaled with `n-1`,
whereas the sum is scaled with `n` if `corrected` is
Expand Down