Hotel Pricing Analysis

This project focused on identifying the key factors that influence hotel pricing in Brussels. Using real-world data, I applied multiple regression models to evaluate how variables such as star rating, customer rating, distance, and promotional offers impact hotel prices. The goal was to determine the most accurate model for predicting pricing and provide insights for both businesses and consumers.

Tools & Skills Used:
-RStudio
-Multiple Linear Regression
-Model Comparison (AIC & BIC)
-Breusch-Pagan Test (Heteroskedasticity)
-Robust Standard Errors
-Data Cleaning & Merging
-Correlation Analysis