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  1. Comparing groups
    randomization and bootstrap methods using R
    Autor*in: Zieffler, Andrew
    Erschienen: 2011
    Verlag:  Wiley, Hoboken, NJ

    Standort:
    Freie Universität Berlin, Universitätsbibliothek
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV)
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Beteiligt: Harring, Jeffrey (Verfasser); Long, Jeffrey D. (Verfasser)
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    ISBN: 9780470621691
    RVK Klassifikation: ES 945 ; MR 2100 ; ST 250
    Schlagworte: Datenverarbeitung; Statistik; Bootstrap (Statistics); Random data (Statistics); Psychology; R (Computer program language); Distribution (Probability theory); SOCIAL SCIENCE / Statistics; Große Abweichung; Statistik
    Umfang: XXXII, 298 S., ill., 25 cm
    Bemerkung(en):

    "This book, written by three behavioral scientists for other behavioral scientists, addresses common issues in statistical analysis for the behavioral and educational sciences. Modern Statistical & Computing Methods for the Behavioral and Educational Sciences using R emphasizes the direct link between scientific research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology, and computation to propose answers to specific research questions. Furthermore, practical suggestions for the analysis and presentation of results, in prose, tables and/or figures, are included. Optional sections for each chapter include methodological extensions for readers desiring additional technical details. Rather than focus on mathematical calculations like so many other introductory texts in the behavioral sciences, the authors focus on conceptual explanations and the use of statistical computing. Statistical computing is an integral part of statistical work, and to support student learning in this area, examples using the R computer program are provided throughout the book. Rather than relegate examples to the end of chapters, the authors interweave computer examples with the narrative of the book. Topical coverage includes an introduction to R, data exploration of one variable, data exploration of multivariate data - comparing two groups and many groups, permutation and randomization tests, the independent samples t-Test, the Bootstrap test, interval estimates and effect sizes, power, and dependent samples"-- Provided by publisher.

    Includes bibliographical references (p. 287 - 298)
  2. Comparing groups
    randomization and bootstrap methods using R
    Autor*in: Zieffler, Andrew
    Erschienen: 2011
    Verlag:  Wiley, Hoboken, NJ

    Standort:
    Universitätsbibliothek Regensburg
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Bibliotheksverbund Bayern (BVB)
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Beteiligt: Harring, Jeffrey (Verfasser); Long, Jeffrey D. (Verfasser)
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    ISBN: 9780470621691
    RVK Klassifikation: ES 945 ; MR 2100 ; ST 250
    Schlagworte: Datenverarbeitung; Statistik; Bootstrap (Statistics); Random data (Statistics); Psychology; R (Computer program language); Distribution (Probability theory); SOCIAL SCIENCE / Statistics; Große Abweichung; Statistik
    Umfang: XXXII, 298 S., ill., 25 cm
    Bemerkung(en):

    "This book, written by three behavioral scientists for other behavioral scientists, addresses common issues in statistical analysis for the behavioral and educational sciences. Modern Statistical & Computing Methods for the Behavioral and Educational Sciences using R emphasizes the direct link between scientific research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology, and computation to propose answers to specific research questions. Furthermore, practical suggestions for the analysis and presentation of results, in prose, tables and/or figures, are included. Optional sections for each chapter include methodological extensions for readers desiring additional technical details. Rather than focus on mathematical calculations like so many other introductory texts in the behavioral sciences, the authors focus on conceptual explanations and the use of statistical computing. Statistical computing is an integral part of statistical work, and to support student learning in this area, examples using the R computer program are provided throughout the book. Rather than relegate examples to the end of chapters, the authors interweave computer examples with the narrative of the book. Topical coverage includes an introduction to R, data exploration of one variable, data exploration of multivariate data - comparing two groups and many groups, permutation and randomization tests, the independent samples t-Test, the Bootstrap test, interval estimates and effect sizes, power, and dependent samples"-- Provided by publisher.

    Includes bibliographical references (p. 287 - 298)
  3. Comparing groups
    randomization and bootstrap methods using R
    Autor*in:
    Erschienen: c2011
    Verlag:  Wiley, Hoboken, N.J.

    Standort:
    Technische Universität München, Universitätsbibliothek
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Bibliotheksverbund Bayern (BVB)
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Beteiligt: Zieffler, Andrew (Sonstige); Harring, Jeffrey (Sonstige); Long, Jeffrey D. (Sonstige)
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9781118063668; 9780470621691
    RVK Klassifikation: ES 945 ; ST 250
    Schlagworte: Große Abweichung; Statistik
    Umfang: 1 Online-Ressource (1 online resource (xxxii, 298 p.))
    Bemerkung(en):

    Includes bibliographical references (p. 287-298)
  4. Comparing groups
    randomization and bootstrap methods using R
    Autor*in: Zieffler, Andrew
    Erschienen: © 2011
    Verlag:  Wiley, Hoboken, N.J.

    Standort:
    Universitätsbibliothek Passau
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Bibliotheksverbund Bayern (BVB)

    Standort:
    Technische Hochschulbibliothek Rosenheim
    Fernleihe:
    keine Ausleihe von Bänden, nur Papierkopien werden versandt
    Link zum Verbundkatalog:
    Bibliotheksverbund Bayern (BVB)
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Volltext (URL des Erstveröffentlichers)
    Quelle: Verbundkataloge
    Beteiligt: Harring, Jeffrey (Verfasser); Long, Jeffrey D. (Verfasser)
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9781118063682; 1118063686; 111806366X; 9781118063668
    Weitere Identifier:
    RVK Klassifikation: MR 2100 ; ES 945 ; ST 250
    Schlagworte: SOCIAL SCIENCE / Statistics; Bootstrap (Statistics); Distribution (Probability theory); Psychology / Data processing; R (Computer program language); Random data (Statistics); Datenverarbeitung; Statistik; Bootstrap (Statistics); Random data (Statistics); Psychology / Data processing; R (Computer program language); Distribution (Probability theory); Große Abweichung; Statistik
    Weitere Schlagworte: Electronic books
    Umfang: 1 Online-Ressource (xxxii, 298 pages)
    Bemerkung(en):

    Includes bibliographical references (pages 287-298)

    "This book, written by three behavioral scientists for other behavioral scientists, addresses common issues in statistical analysis for the behavioral and educational sciences. Modern Statistical & Computing Methods for the Behavioral and Educational Sciences using R emphasizes the direct link between scientific research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology, and computation to propose answers to specific research questions. Furthermore, practical suggestions for the analysis and presentation of results, in prose, tables and/or figures, are included. Optional sections for each chapter include methodological extensions for readers desiring additional technical details. Rather than focus on mathematical calculations like so many other introductory texts in the behavioral sciences, the authors focus on conceptual explanations and the use of statistical computing. Statistical computing is an integral part of statistical work, and to support student learning in this area, examples using the R computer program are provided throughout the book. Rather than relegate examples to the end of chapters, the authors interweave computer examples with the narrative of the book. Topical coverage includes an introduction to R, data exploration of one variable, data exploration of multivariate data - comparing two groups and many groups, permutation and randomization tests, the independent samples t-Test, the Bootstrap test, interval estimates and effect sizes, power, and dependent samples"--