Sinossi
Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.
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Informazioni sugli autori
Skyler J. Cranmer is the Carter Phillips and Sue Henry Professor of Political Science at The Ohio State University.
Bruce A. Desmarais is the DeGrandis-McCourtney Early Career Professor in Political Science at Penn State University.
Jason William Morgan is the Vice President for Behavioural Intelligence: Aware, and visiting scholar in Political Science at The Ohio State University.
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Inferential Network Analysis (Analytical Methods for Social Research)
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Cambridge University Press, 2020
ISBN 10: 1107158125
ISBN 13: 9781107158122
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Inferential Network Analysis (Analytical Methods for Social Research)
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Inferential Network Analysis
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Inferential Network Analysis (Analytical Methods for Social Research)
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Inferential Network Analysis (Analytical Methods for Social Research)
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Inferential Network Analysis
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Inferential Network Analysis (Hardcover)
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Cambridge University Press, Cambridge, 2020
ISBN 10: 1107158125
ISBN 13: 9781107158122
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Hardcover. Condizione: new. Hardcover. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9781107158122
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Inferential Network Analysis (Hardcover)
Editore:
Cambridge University Press, Cambridge, 2020
ISBN 10: 1107158125
ISBN 13: 9781107158122
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Hardcover. Condizione: new. Hardcover. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781107158122
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Inferential Network Analysis (Analytical Methods for Social Research)
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Inferential Network Analysis (Hardcover)
Editore:
Cambridge University Press, Cambridge, 2020
ISBN 10: 1107158125
ISBN 13: 9781107158122
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Da: CitiRetail, Stevenage, Regno Unito
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Hardcover. Condizione: new. Hardcover. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781107158122
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