Quantitative Reasoning and Statistics for Urban Planning

Effective urban and regional planning relies on rigorous data analysis, but many professionals lack the foundational statistical literacy needed to move beyond basic reporting. This course equips you with the quantitative reasoning skills necessary to understand demographic trends, evaluate potential policy impacts, and confidently present data-driven recommendations in planning and policy contexts. What you'll learn: Understand core statistical concepts including descriptive statistics, probability, and standard distributions. Apply principles of data wrangling and visualization to prepare and present complex planning datasets effectively. Practice interpreting census data, surveys, and spatial data structures common in policy analysis. Formulate and test hypotheses using inferential statistics, confidence intervals, and p-values. Learn introductory linear regression techniques to model relationships between key planning variables. Develop ethical reasoning skills for interpreting statistical results and communicating data clearly to stakeholders. The curriculum starts with foundational statistical terminology and data preparation techniques, progressing through descriptive analysis and visualization before diving into inferential techniques like hypothesis testing and basic regression modeling. This course is designed exclusively for beginners in urban studies, planning, public policy, or environmental management who require strong quantitative literacy. No prior statistical knowledge is required. Start building your essential quantitative toolkit today.