Introduction to Applied Bayesian Statistics and Estimation for Social Scientists (Statistics for Social and Behavioral Sciences)

✍ Scribed by Scott M. Lynch

• Publisher: Springer
• Year: 2007
• Tongue: English
• Leaves: 375
• Series: Statistics for Social and Behavioral Sciences
• Edition: 1
• Category: Library

✦ Synopsis

Dr. Scott Lynch has made a great job for those (like me) who want a clear introduction to the methods of bayesian data analysis. I hold a Ph.D. in plant breeding, and as many others, I was trained in the traditional frequentist approach for the analysis of experiments: linear regression, ANOVA and univariate and multivariate linear models. After graduation (1997) I included more technical background such as GLM, and GLMM, but since I was lacking a Bayesian introduction, I wasn't able to grasp the Bayesian methods from more advanced texts such as those by Bradley Carlin, or Andrew Gelman. This book is certain an introduction to the basic bayesian methodology but as such, it includes all the basics facts and theory for understanding more complex methods in the Bayesian paradigm. It is a geat text for those who want to start using Bayesian methods, and prepares you with all the required background to tackle more advanced models within the bayesian approach. In this respect, Lynch's book is a five stars.