A Research on the Relevance of the Crime and the Housing Price Based on the Linear Regression Model

Jiali Guo, Zitao Ying, Zhengqi Sun, Yuxiang Zhu

2022

Abstract

As the most expensive area to live in the United States, Manhattan’s housing prices are influenced by many factors, with crime rates being one of the most important factors affecting Manhattan’s housing prices. Under this situation, this paper will explore the relationship between house prices and crime rates in Manhattan through the house prices and crime rate data in 2016-2017, by using python and R to build a simple linear regression model to find the relationship between the average house price and crime rate. As for the conclusion section, this paper will give the results of the analysis of the data with the conclusion and the practical implications of this conclusion.

Paper Citation

in Harvard Style

Guo J., Ying Z., Sun Z. and Zhu Y. (2022). A Research on the Relevance of the Crime and the Housing Price Based on the Linear Regression Model. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 692-698. DOI: 10.5220/0011754800003607

in Bibtex Style

@conference{icpdi22,
author={Jiali Guo and Zitao Ying and Zhengqi Sun and Yuxiang Zhu},
title={A Research on the Relevance of the Crime and the Housing Price Based on the Linear Regression Model},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={692-698},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011754800003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - A Research on the Relevance of the Crime and the Housing Price Based on the Linear Regression Model
SN - 978-989-758-620-0
AU - Guo J.
AU - Ying Z.
AU - Sun Z.
AU - Zhu Y.
PY - 2022
SP - 692
EP - 698
DO - 10.5220/0011754800003607
PB - SciTePress