College
Buchtel College of Arts and Sciences
Date of Last Revision
2024-06-04 07:23:41
Major
Data Science, Statistics
Honors Course
STAT:498-003
Number of Credits
3
Degree Name
Bachelor of Science
Date of Expected Graduation
Spring 2024
Abstract
My project uses a dataset of bankrupt and non-bankrupt companies in Taiwan from 1999 to 2009. This data was collected from the Taiwan Economic Journal. The statistical methods I used to model the data are CHAID, CART, and logistic regression. The models created are tools that can predict if a company is bankrupt, or not-bankrupt based on other data about the company. I created multiple models for each of the methods to find the best model for each method. I then analyzed the output from each method. Lastly, I determined which model was the best for this data based on the model's accuracy in predicting the bankruptcy status of companies.
Research Sponsor
Mark Fridline
First Reader
Richard Einsporn
Second Reader
Jun Ye
Honors Faculty Advisor
Nao Mimoto
Proprietary and/or Confidential Information
No
Recommended Citation
Elsfelder, Andrew, "Statistical Modeling of Bankruptcy Data" (2024). Williams Honors College, Honors Research Projects. 1829.
https://ideaexchange.uakron.edu/honors_research_projects/1829