House Price Prediction

Multiple Models

The dataset provided for this challenge contained over 70+ variables for us to use in our predictive modeling. Each group member built and tested their own models and then compared the results to see which models performed the best in terms of predicting house prices.

Statistics and R

R is a great language for any kind of statistical modeling. During the course of the project, our group was able to utilize many useful R packages including one that was developed by our professor! R was great for building various predictive models and for generating data visualizations.

Kaggle Regression Challenge

This project was based off the popular Kaggle regression challenge which provided a large dataset of recorded housing data which included house price, number of bedrooms, location, etc. It was our groups task to build linear regression models to make predictions about how much a house would cost based on all other factors provided.