“Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines

• Main Authors: Min Li, Amy Mickel, Stanley Taylor
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2018-01-01
• Series: Journal of Statistics Education
• Subjects: Case study; Classification; Decision rule; Logistic regression; Real data; Risk indicator
• Online Access: http://dx.doi.org/10.1080/10691898.2018.1434342

In this article, a large and rich dataset from the U.S. Small Business Administration (SBA) and an accompanying assignment designed to teach statistics as an investigative process of decision making are presented. Guidelines for the assignment titled “Should This Loan Be Approved or Denied?,” along with a subset of the larger dataset, are provided. For this case-study assignment, students assume the role of loan officer at a bank and are asked to approve or deny a loan by assessing its risk of default using logistic regression. Since this assignment is designed for introductory business statistic courses, additional methods for more advanced data analysis courses are also suggested.