Interactive Visual Least Absolutes Method: Comparison with the Least Squares and the Median Methods

• Myung-Hoon Kim ^[1] ; Michelle S. Kim ^[2]
  1. [1] Kennesaw State University

     Kennesaw State University

     Estados Unidos

     
  2. [2] Dartmouth College

     Dartmouth College

     Town of Hanover, Estados Unidos

     
• Localización: Journal of chemical education, ISSN 0021-9584, Vol. 93, Nº 10, 2016, págs. 1737-1743
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • A visual regression analysis using the least absolutes method (LAB) was developed, utilizing an interactive approach of visually minimizing the sum of the absolute deviations (SAB) using a bar graph in Excel; the results agree very well with those obtained from nonvisual LAB using a numerical Solver in Excel. These LAB results were compared with those from the popular least-squares method (LSQ), which minimizes the sum of the squares of the deviations (SSQ), and also with results from the median method (MED). LAB yielded similar results as LSQ for a data set with relatively smaller average deviations (<5%) as well as for data sets with relatively larger average deviations (>10%). However, for data sets with an outlier, the LAB method yielded significantly different results than LSQ. The LAB results, in all three cases, agree more closely with the results from MED of Theil and Siegel, which handles outliers better than the LSQ approach. The LAB approach (visual or numerical) is as simple and easy to implement in a spreadsheet as LSQ. The visual LAB approach may be practiced for analyzing data that requires regression in any college laboratory courses, especially when the data contain suspected outliers, because it is pedagogically more effective for visual learners than the numerical LAB with Solver.