Urban Quantitative Reasoning and Statistical Methods

Urban planners and policy analysts must make sense of complex spatial and economic data to guide community development. This course introduces you to the core quantitative methods used to analyze housing markets, property values, and neighborhood attributes. You will learn how to read, interpret, and apply statistical models to real-world urban planning scenarios. By building a solid foundation in quantitative reasoning, you will be able to evaluate how different housing characteristics contribute to overall market value. What you will learn: Understand the foundational principles of quantitative reasoning in urban planning; Practice setting up and interpreting hedonic pricing models for housing data; Analyze how specific property attributes and neighborhood factors influence home prices; Apply linear regression techniques to urban datasets; Interpret statistical significance, coefficients, and model fit in planning reports. The course begins with essential terminology, basic statistical concepts, and foundational definitions before guiding you through the practical application of regression analysis on urban datasets. This course is designed for beginners, students of urban studies, and aspiring planners who want to build quantitative skills without prior advanced statistical training. Start developing your analytical toolkit and make data-driven decisions for better communities.