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. The readers will understand Bayesian theory and practice using social science data.

Sommario

1. Introduction: the purpose and scope of this book; 2. Basic probability principles and Bayes law; 3. What is a likelihood function and why care; 4. The core of Bayesian inference: prior times likelihood; 5. Prior probabilities and the progression of human knowledge; 6. Integrals and expected value: not as scary as they look; 7. Software calculation of Bayesian models; 8. Evaluating and comparing model results; 9. Case study I: election polling and Bayesian updating; References.

Riassunto

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. The readers will understand Bayesian theory and practice using social science data.

Dettagli sul prodotto

• Autori: Le Bao, Jeff Gill, Jeff (American University) Bao Gill
• Editore: Cambridge University Press ELT
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 31.05.2024
• EAN: 9781009341196
• ISBN: 978-1-0-0934119-6
• Pagine: 110
• Serie: Elements in Quantitative and Computational Methods for the Social Sciences
• Categorie: Scienze naturali, medicina, informatica, tecnica > Scienze naturali, tematiche generali; Scienze sociali, diritto, economia > Scienze politiche > Scienze politiche e cittadinanza attiva; POLITICAL SCIENCE / General, Social research & statistics, Mathematical & statistical software, Social research and statistics, Research methods: general, Bayesian Inference, Mathematical and statistical software