The purpose of this project is to verify wheather a given data set follows the distribution of Benforrd's Law.
Benford’s Law states that, in a naturally occurring set of numbers, the smaller digits appear disproportionately more often as the leading digits. The leading digits have a distribution where the number 1 appears slightly more than 30% of the time and the number 9 appears less than 5% of the time (which is a difference of 6x).
Benford's law is an observation about the leading digits of the numbers found in real-world data sets. Intuitively, one might expect that the leading digits of these numbers would be uniformly distributed so that each of the digits from 1 to 9 is equally likely to appear. In fact, it is often the case that 1 occurs more frequently than 2, 2 more frequently than 3, and so on. This observation is a simplified version of Benford's law. More precisely, the law gives a prediction of the frequency of leading digits using base-10 logarithms that predicts specific frequencies which decrease as the digits increase from 1 to 9.
This phenomenon occurs generally in many different instances of real-world data. It becomes more pronounced and more likely when more data is combined together from different sources. Not every data set satisfies Benford's law, and it is surprisingly difficult to explain the law's occurrence in the data sets it does describe, but nevertheless it does occur consistently in well-understood circumstances.
Wikipedia has a page on the Benford's law.
Benford’s Law is applied as a method to analyze and find data manipulation in large datasets. It is consistently recognized as a valid method to combat financial fraud and tax evasion. General results showed that COVID-19’s numbers do follow Benford’s Law.
- Java - version 1.8
Project is under development.
Created by @Danisoft Arad 2021 (https://danipedro2006.github.io/) - feel free to contact me!