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Multivariate Spatial Data Analysis in GeoDa Workshop
Spatial data analysis and multivariate applications are increasingly needed to address complex, geographically correlated phenomena. This workshop will cover spatial data handling in GeoDa, exploratory spatial data basics of areal data (eg. choropleth maps, parallel coordinate plots, etc), and some advanced multivariate analysis. Participants will conduct a principal component analysis and k-means cluster analysis with spatial data, mapping outcomes at each stage for additional exploration and understanding of regional dynamics. We will use relevant social determinants of health variables for the continental U.S. using 2018 5-year average Census data and calculate US-wide multidimensional indices and neighborhood typologies at the census tract scale.

Oct 29, 2020 10:00 AM in Eastern Time (US and Canada)

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Dr. Marynia Kolak
Assistant Director of Health Informatics, Senior Lecturer in GIScience @Center for Spatial Data Science, University of Chicago
Marynia Kolak, MS, MFA, PhD, is a health geographer and data scientist using open science tools and an exploratory data analytic approach to investigate issues of equity across space and time. Her research centers on how “place” impacts health outcomes in different ways, for different people, from opioid risk environments to chronic disease clusters. She focuses on quantifying and distilling the structural determinants of health across different environments, tying socio-ecological models of public health with geocomputational methods and quasi-experimental policy evaluation techniques. Marynia is the Assistant Director of Health Informatics and Senior Lecturer in GIScience at the Center for Spatial Data Science, University of Chicago. She received her Ph.D in Geography at Arizona State University, M.F.A in Writing from Roosevelt University, M.S. in GIS from John Hopkins University, and B.S. in Geology from the University of Illinois at Urbana-Champaign.