Introduction to Applied Bayesian Statistics and Estimation for Social Scientists / Edition 1
by Scott M. LynchView All Available Formats & Editions
ISBN-10: 1441924345
ISBN-13: 9781441924346
Pub. Date: 11/19/2010
Publisher: Springer New York
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
Overview
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.
Product Details
- ISBN-13:
- 9781441924346
- Publisher:
- Springer New York
- Publication date:
- 11/19/2010
- Series:
- Statistics for Social and Behavioral Sciences Series
- Edition description:
- Softcover reprint of hardcover 1st ed. 2007
- Pages:
- 359
- Product dimensions:
- 6.10(w) x 9.20(h) x 0.90(d)
Table of Contents
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.Customer Reviews
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