This data dive analyzes apartment prices in San Francisco and New York to identify which housing features most influence price. We compare Poisson and negative binomial regression models and evaluate their performance, finding that the negative binomial model provides a significantly better fit due to overdispersion issues in the Poisson models. The results highlight how model choice impacts pricing insights in real estate data.

Practice work