Clarity should (?) improve as the spread of values increases
The law still holds for any given base
Would be interesting to cross reference the same input data sets with using bases other than 10
something like
np.logX(1 + 1/digit) * N
where X is a range of numbers say [2..16]
So if you generated a range of graphs across the same data with different base sizes and eyeballed the result, that may lead to higher confirmation that the given data is abnormal if its also abnormal for the majority of numeric bases.
Alternatively, it may show what appears as an apparent anomaly is maybe not as bad as it looks. maybe ?
This is super interesting, you got me reading up on stats all over again :) Thanks.
Given that with Benford's law :
Would be interesting to cross reference the same input data sets with using bases other than 10
something like np.logX(1 + 1/digit) * N
where X is a range of numbers say [2..16]
So if you generated a range of graphs across the same data with different base sizes and eyeballed the result, that may lead to higher confirmation that the given data is abnormal if its also abnormal for the majority of numeric bases.
Alternatively, it may show what appears as an apparent anomaly is maybe not as bad as it looks. maybe ?
This is super interesting, you got me reading up on stats all over again :) Thanks.