Introduction to Applied Bayesian Statistics and Estimation for Social Scientists
Scott M. Lynch
€ 145.43
FREE Delivery in Ireland
Description for Introduction to Applied Bayesian Statistics and Estimation for Social Scientists
Paperback. Series: Statistics for Social and Behavioral Sciences. Num Pages: 359 pages, biography. BIC Classification: JH; PBT. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 20. Weight in Grams: 593.
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.
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
Publisher
Springer-Verlag New York Inc.
Format
Paperback
Publication date
2010
Series
Statistics for Social and Behavioral Sciences
Condition
New
Weight
593g
Number of Pages
359
Place of Publication
New York, NY, United States
ISBN
9781441924346
SKU
V9781441924346
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Introduction to Applied Bayesian Statistics and Estimation for Social Scientists
From the reviews: The book ... contains a very detailed and comprehensive description of MCMC methods useful for applied researchers. ... Undoubtedly the book is interesting ... . The reader will gain an extensive knowledge of the issues covered ... . (Dimitris Karlis, Zentralblatt MATH, Vol. 1133 (11), 2008) ... Read more