Models for Social Networks With Statistical Applications

Nonfiction, Reference & Language, Reference, Research, Social & Cultural Studies, Social Science
Cover of the book Models for Social Networks With Statistical Applications by Suraj Bandyopadhyay, Bikas K. Sinha, A. R. Rao, SAGE Publications
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Author: Suraj Bandyopadhyay, Bikas K. Sinha, A. R. Rao ISBN: 9781483305370
Publisher: SAGE Publications Publication: June 2, 2010
Imprint: SAGE Publications, Inc Language: English
Author: Suraj Bandyopadhyay, Bikas K. Sinha, A. R. Rao
ISBN: 9781483305370
Publisher: SAGE Publications
Publication: June 2, 2010
Imprint: SAGE Publications, Inc
Language: English

Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze network data. Clearly demonstrates how graph-theoretic and statistical techniques can be employed to study some important parameters of global social networks. The authors uses real life village-level social networks to illustrate the practicalities, potentials, and constraints of social network analysis ("SNA"). They also offer relevant sampling and inferential aspects of the techniques while dealing with potentially large networks.

Intended Audience

This supplemental text is ideal for a variety of graduate and doctoral level courses in social network analysis in the social, behavioral, and health sciences

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze network data. Clearly demonstrates how graph-theoretic and statistical techniques can be employed to study some important parameters of global social networks. The authors uses real life village-level social networks to illustrate the practicalities, potentials, and constraints of social network analysis ("SNA"). They also offer relevant sampling and inferential aspects of the techniques while dealing with potentially large networks.

Intended Audience

This supplemental text is ideal for a variety of graduate and doctoral level courses in social network analysis in the social, behavioral, and health sciences

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