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Interactive web app to predict the cost of college tuition using regression modeling of historic tuition costs. Written in R and built using Shiny.

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Predictive Modeling of the Cost of College Tuition

by MAS, 2019

App Deployment

This is a web application that will allow you to predict the cost of college tuition in the future.

Introduction

As of now, over 44 million individuals collectively hold 1.5 trillion dollars in college student loan debt. Unfortunately, the cost of college tuition continues to increase despite no apparent improvement in the quality of education. Several reports have argued that the skyrocketing cost of tuition is directly correlated with an increase in college administrative personnel. Additional factors that have contributed to high tuition costs include decreased state funding for public universities, unnecessarily lavish amenities, and - perhaps surprisingly - large increases in student enrollment.

Ironically, very little of the exorbitant tuition costs are funneled into the paychecks of faculty. Approximately, 75% of the instructional staff at colleges and universities are adjunct professors who are temporary employees without benefits. According to glassdoor.com, the average yearly income of an adjunct professor is under $30,000 USD per year.

Additionally, tuition is not used to fund expensive research conducted on university campuses. For example, biomedical research programs are funded largely by grants from the federal government. Indeed, the vast majority of research personnel at universities are not paid by the university but rather through federal grant money. Many of these employees, including the disastrously abused class of workers known as postdoctoral fellows, have minimal health insurance, zero retirement benefits, and annual salaries around $50,000 USD with little to no annual increases.

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Interactive web app to predict the cost of college tuition using regression modeling of historic tuition costs. Written in R and built using Shiny.

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