Report: N-Gram Model Development and Prediction Plan

In an era of data-driven policymaking, robust outlier detection serves as a critical safeguard against distorted decision-making. This analysis demonstrates how advanced statistical techniques can surface hidden anomalies in urban health metrics that traditional descriptive methods might overlook. Using the City Health Dashboard's multidimensional dataset, I demonstrate the application of a variety of analytical approaches.

Guide to OMDb API