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Analysis of Rising Tutition Rates in The United States Based on Clustering Analysis and Regression Models

Authors

Long Cheng and Chenyu You, Rensselaer Polytechnic Institute, USA

Abstract

Since higher education is one of the major driving forces for country development and social prosperity, and tuition plays a significant role in determining whether or not a person can afford to receive higher education, the rising tuition is a topic of big concern today. So it is essentially necessary to understand what factors affect the tuition and how they increase or decrease the tuition. Many existing studies on the rising tuition either lack large amounts of real data and proper quantitative models to support their conclusions, or are limited to focus on only a few factors that might affect the tuition, which fail to make a comprehensive analysis. In this paper, we explore a wide variety of factors that might affect the tuition growth rate by use of large amounts of authentic data and different quantitative methods such as clustering analysis and regression models.

Keywords

Higher Education, Tuition Growth Rate, K-means Clustering, Linear Regression, Decision Tree, Random Effect

Full Text  Volume 6, Number 6