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Record Nr. |
UNINA9910746084603321 |
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Autore |
Stockemer Daniel |
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Titolo |
Quantitative Methods for the Social Sciences : A Practical Introduction with Examples in R / / Daniel Stockemer and Jean-Nicolas Bordeleau |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2023] |
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©2023 |
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ISBN |
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Edizione |
[Second edition.] |
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Descrizione fisica |
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1 online resource (152 pages) : illustrations (black and white, and color) |
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Collana |
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Springer Texts in Political Science and International Relations Series |
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Disciplina |
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Soggetti |
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Social sciences - Research - Methodology |
Social sciences - Research - Statistical methods |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Chapter 1: Introduction -- Chapter 2: The Nuts and Bolts of Empirical Social Science -- Chapter 3: A Short Introduction to Survey Research -- Chapter 4: Constructing a Survey -- Chapter 5: Conducting a Survey -- Chapter 6: Introducing R and Univariate Statistics -- Chapter 7: Bivariate Statistics with Categorical Variables -- Chapter 8: Bivariate Statistics with Two Continuous Variables -- Chapter 9: Multivariate Regression Analysis -- Appendix. |
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Sommario/riassunto |
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This textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R. Building on the premise that we need to teach statistical methods in a holistic and practical format, the book guides students through the four main elements of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. In detail, students will learn how to create their own questionnaire on the basis of formulating hypotheses; sampling participants; disseminating their questionnaire; creating datasets; and analyzing their data. The data analytical sections of this revised and extended edition explain the theory, rationale and mathematical foundations of relevant bivariate and multi-variate statistical tests. These include the T-test, F-test, Chi-square test and correlation analyses, as well as bivariate and multivariate regression analyses. In addition, the book |
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offers a brief introduction to statistical computing with R, which includes clear instructions on how to conduct these statistical tests in R. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research and quantitative methods classes in the social sciences. |
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