Skip to content

Performed linear regression and residuals analysis on college tuition fees and admission rate in R.

Notifications You must be signed in to change notification settings

leepingtay/linear_regression_college_admission

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

linear_regression_college_admission

Performed linear regression and residuals analysis on college tuition fees and admission rate in R. Conducted exploratory data analysis and data visualization in R.

Source of datasets

The Integrated Postsecondary Education Data System (IPEDS) by the National Center for Education Statistics (NCES) in United States. https://nces.ed.gov/ipeds/datacenter/DataFiles.aspx

Project Goal

To examine Top 10 most expensive and least expensive colleges in U.S and to identify associations between tuition fees and admission rate.

Introduction

The datasets contains information about colleges' UNITID, name, location, tuition fees, application, admission, etc. The analysis focuses on public and private not-for-profit colleges in the United States.

Author

Lee Ping Tay

About

Performed linear regression and residuals analysis on college tuition fees and admission rate in R.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published