Using Real Estate Data to Improve Business Student Interpretation in Regression

• Activity Number: 167 - Data Mining and Econometrics
• Type: Contributed
• Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Mitra Lal Devkota* and Eric B Howington
• Companies: University of North Georgia and Valdosta State University
• Keywords: Regression; Slope; Interpretation; Dummy variable; Real Estate

Abstract

Multiple regression is a statistical technique used in many disciplines for the purpose of predicting a quantitative dependent variable. In this regard, business and economics are not exceptions. Hence, it is critical for business and economics students to understand regression methodology, write regression models and prediction equations, and interpret the results correctly. However, business and economics students often struggle with these very skills. This paper identifies and discusses several topics in regression analysis where students struggle with understanding and interpretation and suggests strategies instructors can use to explain these concepts. A real-world data set describing housing prices in Mount Pleasant, South Carolina, USA in 2017 is used for examples.