Naranjo-Zolotov, Mijail JuanovichAcedo Sánchez, AlbertDurham, Mikala Rae2023-11-022023-10-23http://hdl.handle.net/10362/159458Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsSubjective well-being, or how someone reports their own life satisfaction, has important applications in areas like international development, public health, behavioral economics, and politics, but large scale surveys are labor-intensive and costly, and results often underrepresent certain populations. By exploring available open-source spatial data features, we can build on the existing research to test the feasibility of predicting subjective well-being with located data that is free and crowd-sourced. Findings show that while urban green space, healthcare or social amenity density did not show significant correlations to overall subjective well-being, urban green space and amenity density were found to be significant predictors of related self-report features like environmental quality, or social activity. While external variables are difficult to properly correlate to self-reported subjective well-being, there is potential for further exploratory research on subjective well-being domains and possible spatial drivers.engSubjective Well-beingSpatial analysisOpen-Source dataSDG 3 - Good health and well-beingmaster thesis203377265