03.16 ZRFC Risk, Fraud & Compliance, Erich-Schmid-Verlag, Berlin, Germany, pp. 115-120.

**ISSN/ISBN:** Not available at this time.
**DOI:** Not available at this time.

Note - this is a foreign language paper: GER

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**Abstract:** Newcomb-Benford's Law (NBL) describes the frequencies of digits and mantissas in real, not manipulated data sets by theoretical vectors of frequencies which would be valid only if the range of the PDF of the logarithms of the data were infinite. NBL-based data analysis has therefore always a bias. This bias decreases when standard deviation of the PDF of the data logarithms increases and vice versa. This fact is the reason of the high rate of alpha errors during application of NBL based data analysis.
The author presents the tool REEGOOD on a base of which NBL based data analysis becomes a statistically valid testing method with high test power.
In contrast to NBL, a minimum range is no longer necessary for validity. The author offers solutions for lognormal, for logarithmic uniform and for logarithmic triangular distributions of datasets. He suggests a software for all datasets which would prepare the datasets for correct processing in usual auditing software.

**Bibtex:**

```
@article {,
AUTHOR = {Guenther Poekl},
TITLE = {Newcomb-Benford's Law ohne Limits},
JOURNAL = {03.16 ZRFC Risk, Fraud & Compliance},
PUBLISHER = {Erich-Schmid-Verlag, Berlin, Germany},
YEAR = {2016},
PAGES = {115--120},
URL = {https://www.ZRFCdigital.de/ZRFC.03.2016.115},
}
```

**Reference Type:** Magazine Article

**Subject Area(s):** Accounting