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Analyzing DOE With Statistical Software Packages: Controversies and Proposals

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  • Sara Fontdecaba
  • Pere Grima
  • Xavier Tort-Martorell

Abstract

This article studies and evaluates how five well-known statistical packages-JMP, Minitab, SigmaXL, Statgraphics, and Statistica-address the problem of analyzing the significance of effects in unreplicated factorial designs. All five use different methods and criteria that deliver different results, even for simple textbook examples. The article shows that some of the methods used are clearly incorrect and deliver incorrect results. Finally, it raises the question of the impact that this may have in hindering the use of design of experiments (DOE) by nonexpert practitioners, and it provides suggestions for making this analysis more effective and easier to understand. Supplementary materials for this article are available online.

Suggested Citation

  • Sara Fontdecaba & Pere Grima & Xavier Tort-Martorell, 2014. "Analyzing DOE With Statistical Software Packages: Controversies and Proposals," The American Statistician, Taylor & Francis Journals, vol. 68(3), pages 205-211, May.
    • Handle: RePEc:taf:amstat:v:68:y:2014:i:3:p:205-211
    DOI: 10.1080/00031305.2014.923784
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    References listed on IDEAS

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    1. Guillermo de Leon & Pere Grima & Xavier Tort-Martorell, 2011. "Comparison of normal probability plots and dot plots in judging the significance of effects in two level factorial designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(1), pages 161-174.
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    Cited by:

    1. Nuno Costa & Paulo Fontes, 2020. "Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods," Sustainability, MDPI, vol. 12(18), pages 1-19, September.

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