Starting With What You Have

Most quantitative methods textbooks assume a data environment most of the world's cities do not have: a census every five years, a household panel running for decades, administrative microdata geocoded to the individual. This book starts from the opposite premise. What can a researcher do with satellite imagery, citizen maps, complaint records, and twenty comparable cases? Starting With What You Have walks through twelve quantitative and spatial methods, from spatial statistics and geographically weighted regression to fuzzy-set QCA, remote sensing, machine learning with explainable AI, and text and image analysis, each matched to the data conditions it actually requires. Every method chapter ships with runnable code, synthetic data with a known answer planted in it, and a route that needs no programming at all. The book closes by turning the argument outward: if better data would open better methods, what should national statistical systems build first, and in what order? Written for graduate students, researchers, and practitioners working in data-constrained settings, particularly across the Global South.