1# RECORD 24c898db0280ed27b83fec434fc31363de05ba6c2# TITLE: Study on the Influencing Factors of Boston Housing Price3# YEAR: 2025.0 VENUE: Advances in Economics, Management and Political Sciences DOI: 10.54254/2754-1169/2025.297364# AUTHORS: Haoran Hua5# PAGES: 8 CANDIDATE TABLE PAGES (1-based): []6# ABSTRACT: This paper presents a thorough analysis of the Boston Housing Dataset, specifically examining how median house prices (medv) relate to several key factors, with a primary focus on the per capita crime rate (crim). The Boston Housing Dataset serves as a foundational framework for applied data science projects. Through rigorous statistical methods and insightful figures, we aim to uncover the significant influences these factors may have on housing prices. This article explores the factors that may influence housing prices, examines their characteristics and impacts, and provides predictions regarding future housing price trends. Analyses reveal that rising crime rates often have a negative impact on the median housing values within a community.While rising crime rates can lead to a decline in median housing values, the extent of the impact and the underlying mechanisms may differ depending on the region and local circumstances.789===== PAGE 1 (score 3, numeric-paren 0, table-words 0, var-words 3) =====1011Proceedings of the 4th International Conference on Business and Policy Studies12DOI: 10.54254/2754-1169/2025.2973613© 2025 The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.014(https://creativecommons.org/licenses/by/4.0/).1520716Study on the Influencing Factors of Boston Housing Price17Haoran Hua18Xi'an Tie Yi International Curriculum Center, Xi'an, China19huahaoran2025@163.com20Abstract. This paper presents a thorough analysis of the Boston Housing Dataset,21specifically examining how median house prices (medv) relate to several key factors, with a22primary focus on the per capita crime rate (crim). The Boston Housing Dataset serves as a23foundational framework for applied data science projects. Through rigorous statistical24methods and insightful figures, we aim to uncover the significant influences these factors25may have on housing prices. This article explores the factors that may influence housing26prices, examines their characteristics and impacts, and provides predictions regarding future27housing price trends. Analyses reveal that rising crime rates often have a negative impact on28the median housing values within a community.While rising crime rates can lead to a decline29in median housing values, the extent of the impact and the underlying mechanisms may30differ depending on the region and local circumstances.31Keywords: Boston housing price, influencing factor, capita crime rate321. Introduction33The Boston housing dataset is a very framework for applied data science projects. Here, we provide34a novel study. In this introduction, we first provide some background and then our research objects.35Finally, at the end of the introduction we provide an overview of the rest of this paper.361.1. Background37The data of program comes from the UCI machine learning repository.This data was collected in381978. The 506 data represent 14 characteristics of homes in different regions.39The target variable, Median House Value (MEDV), serves as a primary indicator for assessing40housing market values.411.2. Research objective421.This study aims to explore the dataset's features and employ advanced statistical methods to43uncover insights into housing market dynamics in Boston.442.The importance and practical application of integrating standardized statistical analysis45methods into Python teaching are discussed. Through case study and empirical analysis, it is found46that this teaching mode significantly improves students' data analysis ability and problem-solving47skills.48