Newcomb-Beford Law

The Newcomb-Beford Law is based on the uneven distribution of digits observed in many real world datsets under certain conditions.



  1. The numbers need to be random and not assigned, with no imposed minimums or maximums.

  2. The numbers should cover several orders of magnitude, and the dataset should be large. Recommendations in the literature call for 100 to 1,000 samples as a minimum, though Benford’s law has been shown to hold true for datasets containing as few as 50 numbers.

  3. For more details, check Wikipedia!