2026-05-24T16:21:13Zhttps://keep.lib.asu.edu/oai/requestoai:keep.lib.asu.edu:node-1484312024-12-19T19:04:43Zoai_pmh:alloai_pmh:repo_items148431
https://hdl.handle.net/2286/R.I.63247
http://rightsstatements.org/vocab/InC/1.0/
2021-05
27 pages
eng
Mazza, Rachel Marie
Schneider, Laurence
Sha, Xiqing
School of Accountancy
Department of Information Systems
Barrett, The Honors College
Text
Created predictive models using R to determine significant variables that help determine whether someone will default on their loans using a data set of almost 900,000 loan applicants.
Data Analytics
Loans
predictive
A Predictive Statistical Analysis on Loan Data