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Robust estimation procedures and visual display techniques for a two-way classification model

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Abstract

An important problem in statistics is to study the effect of one or two factors on a dependent variable. This type of problem can be formulated as a regression problem (by using dummy (0,1) variables to represent the levels of factors) and the standard least squares (LS) analysis is well-known. The least absolute value (LAV) analysis is less well known, but certainly is becoming more widely used, especially in exploratory data analysis.The purpose of this report is to present a didactic treatment of visual display methods useful in exploratory data analysis. These visual display techniques (stem- and- leaf, box- and- whisker, and two-way plots) are presented for both the least squares and the least absolute value analyses of a two-way classification model.

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Authors and Affiliations

  1. Michael Sklar Consulting, 5337 Harris Circle, 30338, Dunwoody, GA, USA

    Michael G. Sklar

  2. Graduate School of Management, Rutgers University, 07102, Newark, N.J., USA

    Ronald D. Armstrong

Authors
  1. Michael G. Sklar
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  2. Ronald D. Armstrong
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Sklar, M.G., Armstrong, R.D. Robust estimation procedures and visual display techniques for a two-way classification model. Qual Quant 28, 283–304 (1994). https://doi.org/10.1007/BF01098945

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