Bradford Distribution / Bradford Law of Scattering

Probability Distributions >

The Bradford distribution is a special type of right-skewed curve which was first uncovered in 1949 by S.C. Bradford when he used it to explain how diverse information on a certain topic can be found across various sources and references – instead of being haphazardly scattered, the data follows an archetypal pattern. This unique law sheds light into where people might look for specific types of details relating to any number of topics or subjects.

Bradford’s law of scattering is a special case of the beta distribution of the second kind or Pearson’s Type VI.

PDF for the Bradford Distribution

The probability density function is:

bradford distribution

  • x is a proportion.

Real Life Example of the Bradford Distribution

An example of how the Bradford distribution works: interestingly, the top 10 journals in a certain field can contain the same amount of research articles as over 250 other less popular ones. Analyzing any particular topic may reveal that 20 papers have been published on it within last year – evenly distributed across all 260+ periodicals. This implies that while there is much knowledge to be uncovered beyond just a handful of renowned places, their importance remains invaluable due to concentration and accessibility of material; making them an essential hub for further investigation into the subject matter.


Abramowitz, M. and Stegun, I. A. (Eds.). “Probability Functions.” Ch. 26 in Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, 9th printing. New York: Dover, pp. 925-964, 1972.
Evans, M.; Hastings, N.; and Peacock, B. “Probability Density Function and Probability Function.” §2.4 in Statistical Distributions, 3rd ed. New York: Wiley, pp. 9-11, 2000.
Nicolaisen, J., & Hjørland, B. (2007). Practical potentials of Bradford’s law: A critical examination of the received view. Journal of Documentation, 63.
Saracevic, T. (1975). Relevance: A review of and a framework for the thinking on the notion in information science. Journal of the American Society for Information Science, 26(6), 321-343.

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