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(1981) Washington, LC Benford’s law for Fibonacci and Lucas numbers. Fibonacci Quarterly 19, 175-177.

(1982) Becker, PW Patterns in Listings of Failure-Rate and MTTF Values and Listings of Other Data. IEEE Transac-tions on Reliability 31(2), 132-134. ISSN: 0018-9529.

(1989) Gutman, R and Lucey, BM. Psychological barriers in gold prices? Review of Financial Economics 16, 217–230.

(1989) EInstein, DJ. Professor of Magic Mathematics. Math Horizons (Feb), 11-15.

(1996) Brecht, WS and Albrecht, CC. Root out fi nancial deception. Journal of Accountancy 193(4), 30-34.

(1997) Allaart, PC. An invariant-sum characterization of Benford's law.

(2000) Allan, J and Bhattacharya, S. A short note on fi nancial data set detection using neutrosophic probability. Proceedings of the fi rst international conference on neutrosophy, neutrosophic logic, neutrosophic set, neutrosophic probability and

(2000) Albrecht, CC, Albrecht, WS and Dunn, Conducting a Pro-Active Fraud Audit: A Case Study.

(2000) Recht, J. Die Eins vom Planet Zob. Die Zeit, 28 Sep 2000.

(2000) Arita, M . Scale-freeness and biological networks. Journal of Biochemistry, 138 (1): 1-4. ISSN: 0021-924X.

(2000) Armstrong, JS. Extrapolation for time-series and cross-sectional data. In: Principles of Forecasting: a Hand-book for Researchers and Practitioners. Kluwer Publishers.

(2000) Ashcraft, MH. Cognitive arithmetic: A review of data and theory. Cognition 44 (Aug), 75-106.

(2000) Anonymous. Numerology for accountants. Journal of Accountancy 186(5), 15.

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Adhikari, AK (1969)Some Results on Distribution of Most Signifi cant Digit

ABSTRACT: It is empirically well established that in large collections of numbers the proportions of ent-

ries with the most significant digit $A$ is $\log_10(A+1)/A$. The property of the most significant digit has

been studied in the present paper. It has been proved that when random numbers or their reciprocals

are raised to higher and higher powers, they have log distributions of most significant digit in the limit.

The property is also demonstrated in the limit by the products of random numbers as the number of

terms in the product becomes higher and higher. The property is not, however, demonstrated by higher

roots of the random numbers or their reciprocals in the limit. In fact there is a concentration at some

particular digit. It has been shown that if $X$ has log distribution of the most significant digit, so does $1/

X$ and $CX$, $C$ being any constant, under stronger conditions.

Adhikari, AK and Sarkar, BP (1968)Distributions of most significant digit in certain functions whose arguments are random variables

Sankhya-The Indian Journal of Statistics Series B, 31 (Dec), 413-420ISSN / ISBN: 0581-5738

MathSciNet: MR0279920 (43 #5641)

Reference Type: Journal ArticleSubject Area(s): Not specified

Adhikari, AK and Sarkar, BP (1968). Distributions of most signifi cant digit in certain functions whose arguments are random variables.

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