Introduction to Applied Bayesian Statistics and Estimation for Social Scientists / Edition 1

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists / Edition 1

by Scott M. Lynch
     
 

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

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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)

Related Subjects

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.

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