This reading group moderated by consultants from CSCAR will focus on spatial analysis especially as practiced in social sciences. We will meet for 1.5 to 2 hours every month on the fourth Thursday and discuss one or two chapters from relevant graduate level textbooks. We will focus on the concepts and applications but will also try to discuss the technical details. The format is open-ended, and the key objective is to support learning at different knowledge and skill levels. If there is interest, we will also cover software implementation of techniques in R or Python. We will select reading material that is available via U-M library or freely accessible online.
Readings – We will discuss the following chapters:
(2) Chapter 3: Global and local indicators of spatial association (from Spatial Analysis using Big Data by Yoshiki Yamagata and Hajime Seya)
(3) Chapter 3: Spatial autocorrelation and statistical inference (from Spatial Analysis for Social Science by David Darmofal)
Digital versions of the above two books are available from the UM Library.