CRD 150: Quantitative Methods in Community Research
Fall 2018; Winter 2020; Winter 2021; Spring 2022, Winter 2023
Data are everywhere. Data are no longer just collected by means of traditional surveys and questionnaires, but through simple acts like hailing a taxi, biking, and looking at your phone. Communities are now relying more and more on traditional and new forms of data to address social problems and policy issues such as crime, displacement, and poverty. This course is an introduction to the use of statistical methods and tools to uncover, understand and conceptualize patterns in data. The empirical and theoretical emphasis will be on the community; that is, the class will give you the methodological skills to use data to better describe communities and examine community-level phenomena. You will work with both nonspatial and spatial data from traditional (e.g. U.S. Census) and nontraditional sources (e.g. open data portals). Specific topics covered include data acquisition, management, and presentation (graphs, tables, maps), descriptive analysis (opportunity mapping, spatial clustering), citizen science and participatory mapping, and measuring place-based inequalities. Lectures will present abstract statistical concepts alongside data analysis examples motivated through real-world problems. Labs will provide hands-on practice of the methods covered in lecture using software programs (R, ArcGIS Online).
Class website: https://crd150.github.io/
CRD 156: Community Economic Development
Winter 2018; Winter 2019; Spring 2020; Spring 2021
Community economic development (CED) is the process by which members of a low-income community, working with one another through community-based organizations and with other supporters, private and public, improve their economic well-being, increase their control over their economic lives, and build community power and decision-making.
This course introduces students to the theory and practice of CED. The first section of the course sets the context for CED, including its historical basis, core principles, stakeholders, strategies and projects. We will go through the what, where, why, and how of CED. The second section of the course provides a deeper introduction to specific strategies in business, workforce, locality, and off-the-market development. Although theory will be presented throughout the quarter, the focus will be on application, including an introduction to the data, tools, and methods used in CED assessment, implementation, and evaluation.
Student Final CED Plans:
CRD 1: The Community
In this course, we focus on the spaces, scales, and dimensions of social, political, economic, and cultural changes in a globalizing, multicultural, and highly technological world. Students will learn to apply community-based concepts to understand the drivers, patterns, processes, and implications of these changes happening at multiple scales, including global, regional, and local.
CRD 230: Spatial Methods in Community Research
Spring 2018; Winter 2019; Winter 2021, Winter 2023
Many community socioeconomic and demographic processes such as poverty, crime, healthy food access, school quality, migration, and segregation have important spatial components. Spatial data are becoming more ubiquitous and the tools for managing, processing, examining, and modelling these data are becoming more accessible. This course introduces students to the important theoretical roles that space and place have in community research. Here, the community is broadly defined as a geographic unit with recognizable boundaries that possesses a resident sense of place. The course will also have a large analytical component, exposing students to the acquisition, management, examination, and modelling of spatial data for understanding communities. The course will focus on applications in the social sciences and public health, including demography, epidemiology, sociology, criminology, human geography, public policy, education, and others. The course assumes you have taken an introductory class in statistics and have familiarity with univariate statistics such as linear regression. Experience with a statistical package (like Stata, SAS or R) is useful but not required.
Class website: https://crd230.github.io/
GEO 200CN: Quantitative Geography
Spring 2020; Spring 2022
This course provides an introduction to quantitative geographic methods with a focus on spatial data manipulation, modeling, and analysis. Students leaving the course should have gained both methodological skills, and have a stronger sense of the concepts underlying this type of research analysis. Lectures will present abstract statistical concepts alongside data analysis examples motivated through real-world problems. Labs will provide hands-on practice of the methods covered in lecture and readings using the statistical software program R.
Class website: https://geo200cn.github.io/