How to properly apply Benford's Law to apartment service charge data? I want to apply Benford's Law to a breakdown of billing information we recieve for our apartment building's service charges. In other words, I want to compare the distribution of my service charge numbers to Benford's Law distribution.
Long story short, the residents and I believe there is either some fraud or negligence occuring with the billing amounts and no one can help us resolve our case.
The service charge breakdown will look something like this
Service                     | Year 2021
----------------------------------------
Estate CCTV Maintenance     | $4.09
Estate Reparis              | $30.25
Grounds Maintenance         | $45.25
Elevator Maintenance        | $258.89
Heating / Hot Water         | $27.35
Reserve Fund                | $819.59
..........

There are about 21 services in total (I've only shown 6 above). Each of the residents is charged a slightly different amount per service based on the size (sq. ft) of their apartment, and there are some 50 residents, yielding $21\times 50 = 1,050$ unique data points.
I know that to apply Benford's Law, you need a dataset that ranges over a few orders of magnitude. Unfortunately, here we only have numbers from $10^{-1} \sim 10^3$.
I have a few questions

*

*Is $1,050$ enough datapoints to compare the distribution of these service charge numbers to Benford's Law log distribution? How can I account for any error?

*Is the range of this dataset large enough to use Benford's Law?

*Can I apply Benford's Law to the leading digit of the of the number, as well as to the leading digit of the decimal in each charge separately?


I think you can, because different categories for your data is equivalent to spanning orders of magnitude, in terms of diversification of the data. For the type of statistical significance test, I would use Cho and Gaines (2007) Euclidean distance dN. Morrow (2014) reviews all available tests, and concludes that the convergence of dN is better than the others.
Morrow, J. (2014). Benford’s Law, families of distributions and a test basis [Paper]. Centre for Economic Performance, London School of Economics and Political Science.
