The Urban Data & Methods component of the MUSPP is structured as a two-course sequence. Part 1, Urban Data & Methods I, focuses on quantitative approaches to analyzing urban systems and trends, and is taught in Term 1.

The aim of this course is to equip students with the quantitative methods and analytical tools required to undertake urban research and generate data-driven insights that inform planning and policy interventions. The course emphasizes the use of secondary and primary quantitative datasets, including census, administrative, and survey data, and develops competencies in handling, analyzing, and interpreting such data using statistical techniques, data analytics, and contemporary computational tools.

A key focus is on building students’ ability to apply quantitative social science methodologies to the urban context—ranging from descriptive analysis to statistical inference and modelling—so as to examine patterns, relationships, and dynamics within cities in a systematic and rigorous manner. The course also introduces emerging practices in urban data analytics, computational analysis, and AI-assisted research workflows, preparing students to engage with evolving data-rich urban environments and support evidence-based decision-making.

Instructors: Dr Dinithi Jayasekara
Time: Thursday (10AM-1PM)
Venue: TBC

Week 1: Introduction and Research Methods
Week 2: Data, Variables, Causality, and Validity
Week 3: Descriptive Statistics
Week 4: Economic Analysis
Week 5: Survey Design & Sampling
Week 6: Designing Experiments
Week 7: Recess week
Week 8: Foundations in Traditional Qualitative Methods
Week 9: From Analog to Digital: Disruptions in Human-Centric Research (Part I)
Week 10: From Big Data to Smart Cities: Disruptions in Human-Centric Research (Part II)
Week 11: Qualitative Research in the Digital Urban Present (Part I)
Week 12: Future Directions: Immersive, Mixed, and Gamified Qualitative Methods
Week 13 & 14: Presentation and Wrapping Up