Statistical modeling and inference for social science /
This book provides an introduction to probability theory, statistical inference and statistical modeling for social science researchers and Ph.D. students. Focusing on the connection between statistical procedures and social science theory, Sean Gailmard develops core statistical theory as a set of...
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| Format: | Book |
| Language: | English |
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Cambridge ; New York :
Cambridge University Press,
2014.
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| Series: | Analytical methods for social research.
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| Summary: | This book provides an introduction to probability theory, statistical inference and statistical modeling for social science researchers and Ph.D. students. Focusing on the connection between statistical procedures and social science theory, Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables, the primary aim of social scientists. Gailmard explains how social scientists express and test substantive theoretical arguments in various models. Chapter exercises require application of concepts to actual data and extend students' grasp of core theoretical concepts. Students will complete the book with the ability to read and critique statistical applications in their fields of interest. |
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| Physical Description: | xviii, 373 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references (pages 361-366) and index. |
| ISBN: | 9781107003149 (hardback) 1107003148 (hardback) |