- Lieferumfang: Sofa mit Armlehne inkl. 3 Rückenkissen und 4 Deko-Kissen 174597636493 Springer
23194 https: www.billiger.de common modules api
cmodul?mc=6yaa604IiBJo&p=-p6STOxmd3FRDMrEUYsO-lVt6WZAp33cWGGzTjRsvqB5p11Pk4U7aWI-yYEstmQrYkZKpwcYI7dIHx9e5GpWVCkWXk2Uqxi9b-BpUXdO7Gzobzp-A5MHfJ3vvvNr1_-bpVygqhKvtvxrQUdlpsG-hPQi1Be4GVRHA&mid=174597636493&id=174597636493&ts=20231117
0.00 0 9783031248566 117.69 With the primary goal of expanding access to spatial data science
tools this book offers dozens of minimal or low-code functions and tutorials designed to ease
the implementation of fully reproducible Spatial Socio-Econometric Modeling (SSEM) analyses.
Designed as a University of Pennsylvania Ph.D. level course for sociologists political
scientists urban planners criminologists and data scientists this textbook equips social
scientists with all concepts explanations and functions required to strengthen their data
storytelling. It specifically provides social scientists with a comprehensive set of
open-access minimal code tools to:-Identify and access place-based longitudinal and
cross-sectional data sources and formats-Conduct advanced data management including crosswalks
joining and matching-Fully connect social network analyses with geospatial statistics-Formulate
research questions designed to account for place-based factors in model specification and
assesstheir relevance compared to individual- or unit-level indicators-Estimate distance
measures across units that follow road network paths -Create sophisticated and interactive HTML
data visualizations cross-sectionally or longitudinally to strengthen research storytelling
capabilities-Follow best practices for presenting spatial analyses findings and
implications-Master theories on neighborhood effects equality of opportunity and geography of
(dis)advantage that undergird SSEM applications and methods-Assess multicollinearity issues via
machine learning that may affect coefficients' estimates and guide the identification of
relevant predictors-Strategize how to address feedback loops by using SSEM as an identification
framework that can be merged with standard quasi-experimental techniques like propensity score
models instrumental variables and difference in differences-Expand the SSEM analyses to
connections that emerge via social interactions such as co-authorship and advice networks or
any form of relational dataThe applied nature of the book along with the cost-free
multi-operative R software makes the usability and applicability of this textbook worldwide."
