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  • 1
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    UID:
    almahu_9948609579202882
    Format: 1 online resource (xviii, 373 pages) : , digital, PDF file(s).
    ISBN: 9781139047449 (ebook)
    Series Statement: Analytical methods for social research
    Content: Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes 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 - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of interest.
    Note: Title from publisher's bibliographic system (viewed on 30 May 2018). , Machine generated contents note: 1. Introduction; 2. Descriptive statistics: data and information; 3. Observable data and data-generating processes; 4. Probability theory: basic properties of data-generating processes; 5. Expectation and moments: summaries of data-generating processes; 6. Probability and models: linking positive theories and data-generating processes; 7. Sampling distributions: linking data-generating processes and observable data; 8. Hypothesis testing: assessing claims about the data-generating process; 9. Estimation: recovering properties of the data-generating process; 10. Causal inference: inferring causation from correlation; Afterword: statistical methods and empirical research.
    Additional Edition: Print version: ISBN 9781107003149
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Book
    Book
    New York, NY :Cambridge University Press,
    UID:
    almafu_BV042074865
    Format: xviii, 373 Seiten : , Diagramme.
    Edition: First published
    ISBN: 978-1-107-00314-9
    Series Statement: Analytical methods for social research
    Note: Literaturverzeichnis Seite 361-366
    Language: English
    Subjects: Political Science , Sociology
    RVK:
    RVK:
    Keywords: Sozialwissenschaften ; Statistik ; Methode
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Book
    Book
    New York, NY : Cambridge Univ. Press
    UID:
    gbv_776994476
    Format: XVIII, 373 S. , graph. Darst.
    ISBN: 9781316622223 , 9781107003149
    Series Statement: Analytical methods for social research
    Content: "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"--
    Note: Literaturverz. S. 361 - 366 , Machine generated contents note: 1. Introduction; 2. Descriptive statistics: data and information; 3. Observable data and data-generating processes; 4. Probability theory: basic properties of data-generating processes; 5. Expectation and moments: summaries of data-generating processes; 6. Probability and models: linking positive theories and data-generating processes; 7. Sampling distributions: linking data-generating processes and observable data; 8. Hypothesis testing: assessing claims about the data-generating process; 9. Estimation: recovering properties of the data-generating process; 10. Causal inference: inferring causation from correlation; Afterword: statistical methods and empirical research.
    Additional Edition: ISBN 9781139989442
    Language: English
    Subjects: Political Science , Sociology
    RVK:
    RVK:
    Keywords: Sozialwissenschaften ; Statistik ; Qualitative Methode ; Einführung
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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