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Scientific Productivity in Theoretical Population Genetics:A Case Study in Core Journals


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1 Scientometrics and Informetrics Group National Institute of Science, Technology and Development Studies, Dr. K.S. Krishnan Marg, New Delhi - 110012, India
     

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Examines the applicability of Lotka's Law and a few other statistical distributions for their goodness-of-fit to the author productivity data from eleven core journals in theoretical population genetics. The negative binomial and geometric distribution are found to be generally applicable in majority of the data sets and also in terms of best fit.

Keywords

Population Genetics, Lotka's Law, Statistical Distribution, Author Productivity, Binomial Distribution, Geometric Distribution.
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About The Authors

B. M. Gupta
Scientometrics and Informetrics Group National Institute of Science, Technology and Development Studies, Dr. K.S. Krishnan Marg, New Delhi - 110012
India

Suresh Kumar
Scientometrics and Informetrics Group National Institute of Science, Technology and Development Studies, Dr. K.S. Krishnan Marg, New Delhi - 110012
India


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Abstract Views: 424

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  • Scientific Productivity in Theoretical Population Genetics:A Case Study in Core Journals

Abstract Views: 424  |  PDF Views: 4

Authors

B. M. Gupta
Scientometrics and Informetrics Group National Institute of Science, Technology and Development Studies, Dr. K.S. Krishnan Marg, New Delhi - 110012, India
Suresh Kumar
Scientometrics and Informetrics Group National Institute of Science, Technology and Development Studies, Dr. K.S. Krishnan Marg, New Delhi - 110012, India

Abstract


Examines the applicability of Lotka's Law and a few other statistical distributions for their goodness-of-fit to the author productivity data from eleven core journals in theoretical population genetics. The negative binomial and geometric distribution are found to be generally applicable in majority of the data sets and also in terms of best fit.

Keywords


Population Genetics, Lotka's Law, Statistical Distribution, Author Productivity, Binomial Distribution, Geometric Distribution.