“Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2018-01-01
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| Series: | Journal of Statistics Education |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/10691898.2018.1434342 |
| _version_ | 1828199697377918976 |
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| author | Min Li Amy Mickel Stanley Taylor |
| author_facet | Min Li Amy Mickel Stanley Taylor |
| author_sort | Min Li |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T10:59:41Z |
| format | Article |
| id | doaj.art-03b66f84566d4f00a964bb36d02f8617 |
| institution | Directory Open Access Journal |
| issn | 1069-1898 |
| language | English |
| last_indexed | 2024-04-12T10:59:41Z |
| publishDate | 2018-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Statistics Education |
| spelling | doaj.art-03b66f84566d4f00a964bb36d02f86172022-12-22T03:35:59ZengTaylor & Francis GroupJournal of Statistics Education1069-18982018-01-01261556610.1080/10691898.2018.14343421434342“Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment GuidelinesMin Li0Amy Mickel1Stanley Taylor2College of Business Administration, California State UniversityCollege of Business Administration, California State UniversityCollege of Business Administration, California State UniversityIn 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.http://dx.doi.org/10.1080/10691898.2018.1434342Case studyClassificationDecision ruleLogistic regressionReal dataRisk indicator |
| spellingShingle | Min Li Amy Mickel Stanley Taylor “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines Journal of Statistics Education Case study Classification Decision rule Logistic regression Real data Risk indicator |
| title | “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines |
| title_full | “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines |
| title_fullStr | “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines |
| title_full_unstemmed | “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines |
| title_short | “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines |
| title_sort | should this loan be approved or denied a large dataset with class assignment guidelines |
| topic | Case study Classification Decision rule Logistic regression Real data Risk indicator |
| url | http://dx.doi.org/10.1080/10691898.2018.1434342 |
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