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Social Science Quarterly

Social Science Quarterly
Author: Benigno Aquirre (ed)
Publisher:
Total Pages: 0
Release: 2000
Genre:
ISBN:

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Social Science Quarterly

Social Science Quarterly
Author:
Publisher:
Total Pages: 494
Release: 1991
Genre: Political science
ISBN:

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Social Science for What?

Social Science for What?
Author: Mark Solovey
Publisher: MIT Press
Total Pages: 409
Release: 2020-07-07
Genre: Political Science
ISBN: 0262358751

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How the NSF became an important yet controversial patron for the social sciences, influencing debates over their scientific status and social relevance. In the early Cold War years, the U.S. government established the National Science Foundation (NSF), a civilian agency that soon became widely known for its dedication to supporting first-rate science. The agency's 1950 enabling legislation made no mention of the social sciences, although it included a vague reference to "other sciences." Nevertheless, as Mark Solovey shows in this book, the NSF also soon became a major--albeit controversial--source of public funding for them.


Social Science Research

Social Science Research
Author: Anol Bhattacherjee
Publisher: CreateSpace
Total Pages: 156
Release: 2012-04-01
Genre: Science
ISBN: 9781475146127

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This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.


Maximum Likelihood for Social Science

Maximum Likelihood for Social Science
Author: Michael D. Ward
Publisher: Cambridge University Press
Total Pages: 327
Release: 2018-11-22
Genre: Political Science
ISBN: 1107185823

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Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation.