The City That Never Sleeps: Forecasting NYC’s Noise Complaints with Bayesian Models

This presentation looks at how everyday noise in New York City changes from neighborhood to neighborhood, across the days of the week during the summer. Using several years of NYC 311 data, it goes beyond simply counting complaints to ask a more practical question: how confident can we be that some areas are actually noisier than others?

Data Engineer Moses McCall will introduce Bayesian modeling in an intuitive, non-technical way, focusing on uncertainty as something we can measure rather than ignore. Interactive maps will be used alongside the analysis to make citywide patterns easy to explore and compare. Finally, the models will be tested against more recent data to see how well these patterns hold up over time, comparing what the models expected with what actually happened.