BYU

Abstract by Angela Teuscher

Personal Infomation


Presenter's Name

Angela Teuscher

Co-Presenters

None

Degree Level

Masters

Co-Authors

None

Abstract Infomation


Department

Statistics

Faculty Advisor

William Christensen

Title

Predicting House Prices using Gamma Regression

Abstract

Gamma regression allows us to account for skewness in response variables without transfor- mations and is often more robust than other regression methods. One application of gamma regression is in predicting housing prices, which are strongly right-skewed. A model that predicts house prices well could be a useful tool for a website such as Zilllow. The final model used 11 predictors and the square root link, but had a root predictive mean squared error (RPMSE) of about $146,000 and simulated residual plots indicated a poor fit. Overall, the model is not good enough to be used as a prediction tool, but additional variables and a focus on middle class houses could result in a more appropriate model.