Buch, Englisch, 359 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 587 g
Buch, Englisch, 359 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 587 g
Reihe: Statistics for Social and Behavioral Sciences
ISBN: 978-1-4419-2434-6
Verlag: Springer
This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
Weitere Infos & Material
Probability Theory and Classical Statistics.- Basics of Bayesian Statistics.- Modern Model Estimation Part 1: Gibbs Sampling.- Modern Model Estimation Part 2: Metroplis–Hastings Sampling.- Evaluating Markov Chain Monte Carlo Algorithms and Model Fit.- The Linear Regression Model.- Generalized Linear Models.- to Hierarchical Models.- to Multivariate Regression Models.- Conclusion.
