Two Variance Results in Population Genetics Theory

Warren J. Ewens, Arindam Roy Choudhury, Richard C. Lewontin and Carsten Wiuf

Mathematical Population Studies, 2007, vol. 14, issue 2, 93-110

Abstract: The assessment of the degree of genetic variation in a natural population, and the nature of that variation, is of central importance in both theoretical and applied population studies. Two “variance” results in population genetics theory are presented. For the first, expressions are found for the expected difference in the estimates of genetic variation in a population obtained by two investigators sampling from the same population in the same generation. The second result concerns the question of whether the degree of genetic variation in a population is best estimated by using the number of alleles observed in a sample of genes or by the number of polymorphic sites observed in the sample. For some combinations of the actual degree of variation and the sample size the former is preferred while for other combinations the latter is preferred. The reason for this is discussed.

Keywords: alleles; estimation; genetics; optimality; sites; variance (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/08898480701298376 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:mpopst:v:14:y:2007:i:2:p:93-110

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GMPS20

DOI: 10.1080/08898480701298376

Access Statistics for this article

Mathematical Population Studies is currently edited by Prof. Noel Bonneuil, Annick Lesne, Tomasz Zadlo, Malay Ghosh and Ezio Venturino

More articles in Mathematical Population Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().