This course introduces students to quantitative analysis and research methods for urban planning. The course begins with an examination of how quantitative methods fit within the broader analytic landscape. It then exposes students to basic descriptive statistics (including measures of central tendency and dispersion), principles of statistical inference, and a wide variety of analytic methods and their practical application. By the end of the course, students will be comfortable with many analytic techniques relevant to urban planning and policy, including: z-tests, t-tests, ANOVA, chi square tests, correlation, and multivariate regression. On a broader level, students will gain the ability to understand and critically question the kinds of analyses and representations of quantitative data encountered in urban planning and allied disciplines.
The aim of the course is to introduce students to key concepts and tools in quantitative analysis and research. Most importantly, however, the goal is to develop students’ intuition regarding data analysis and the application of statistical techniques. By the end of the course, students will be familiar with how common techniques of quantitative analysis can be applied to a wide variety of data. Students will also gain a sense of the strengths and weaknesses of quantitative data analysis and under what circumstances the tools learned in the class are best applied in practice. The course seeks to train technically competent, intellectually critical practitioners and scholars who are able to apply quantitative methods in a wide range of settings, and who are also aware of the wider analytic context into which these approaches fit. There is a focus throughout the course on epistemology and the ethics of claim-making. Over the course, students will deepen their understanding of how claims are made, how claims are connected to different forms of evidence, and what makes different kinds of claims credible.