Predicting Condominium Sale Prices

In this project, you'll take on the role of a data analyst tasked with predicting condominium sale prices in New York City. Using property sales data, you'll apply linear regression modeling techniques in R to determine how well the size of a condominium explains its sale price, both across the city as a whole and within individual boroughs. Throughout the project, you'll develop skills in data cleaning, exploratory analysis, and statistical modeling. You'll identify and handle outliers, use data visualization to understand trends, and build and interpret linear regression models. The project culminates in a comparison of model performance between boroughs. Objective: Use linear regression modeling in R to predict New York City condominium sale prices based on size, and compare model accuracy between different boroughs.