Analyzes spatial and spatial-temporal data, focuses on key datasets, data analysis using WinBUGS, R, GeoDa. Examines spatial and spatial-temporal data modeling in social, economic sciences. Looks at modeling decisions made in the course of research, undertakes data analysis, interpret results.

Robert Haining is Emeritus Professor in Human Geography, University of Cambridge, England. He is the author of Spatial Data Analysis in the Social and Environmental Sciences (1990) and Spatial Data Analysis: Theory and Practice (2003). He is a Fellow of the RGS-IBG and of the Academy of Social Sciences.

Guangquan Li is Senior Lecturer in Statistics in Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle, England. His research includes the development and application of Bayesian methods in the social and health sciences. He is a Fellow of the Royal Statistical Society.

Introduction. Thinking spatially, thinking statistically in the social and economic sciences. The nature of spatial data and the implications for statistical analysis. Exploratory analysis of spatial and spatial-temporal data. Bayesian regression modeling with spatial data. Introduction to the Bayesian approach to regression modeling with spatial data. Topics in spatial modeling. Further topics in spatial modeling. Bayesian regression modeling with spatial-temporal data. Generic issues in spatial-temporal modeling. Topics in spatial-temporal modeling. Appendices.