Bayesian social science statistics: from the very beginning
In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of th...
Gespeichert in:
| Hauptverfasser: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2024
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| Schlagworte: | |
| Online-Zugang: | DE-12 DE-473 URL des Erstveröffentlichers |
| Zusammenfassung: | In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 17 Oct 2024) |
| Beschreibung: | 1 Online-Ressource (99 Seiten) |
| ISBN: | 9781009341189 |
| DOI: | 10.1017/9781009341189 |
Internformat
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| author | Gill, Jeff Bao, Le |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1017/9781009341189 |
| format | Electronic eBook |
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| id | DE-604.BV050063123 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-28T11:09:14Z |
| institution | BVB |
| isbn | 9781009341189 |
| language | English |
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| publisher | Cambridge University Press |
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| spelling | Gill, Jeff (DE-588)1191194701 aut Bayesian social science statistics from the very beginning Jeff Gill, Le Bao Cambridge Cambridge University Press 2024 1 Online-Ressource (99 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 17 Oct 2024) In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout Social sciences / Statistical methods Bayesian statistical decision theory Probabilities Bao, Le aut Erscheint auch als Druck-Ausgabe 9781009494694 Erscheint auch als Druck-Ausgabe 9781009341196 https://doi.org/10.1017/9781009341189?locatt=mode:legacy Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Gill, Jeff Bao, Le Bayesian social science statistics from the very beginning Social sciences / Statistical methods Bayesian statistical decision theory Probabilities |
| title | Bayesian social science statistics from the very beginning |
| title_auth | Bayesian social science statistics from the very beginning |
| title_exact_search | Bayesian social science statistics from the very beginning |
| title_full | Bayesian social science statistics from the very beginning Jeff Gill, Le Bao |
| title_fullStr | Bayesian social science statistics from the very beginning Jeff Gill, Le Bao |
| title_full_unstemmed | Bayesian social science statistics from the very beginning Jeff Gill, Le Bao |
| title_short | Bayesian social science statistics |
| title_sort | bayesian social science statistics from the very beginning |
| title_sub | from the very beginning |
| topic | Social sciences / Statistical methods Bayesian statistical decision theory Probabilities |
| topic_facet | Social sciences / Statistical methods Bayesian statistical decision theory Probabilities |
| url | https://doi.org/10.1017/9781009341189?locatt=mode:legacy |
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