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Kukla Degiskenlerin T Istatistigi ile Aykiri Gozlemler Tespit Edilemez

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  • Arzdar KIRACI

    (Baskent University)

Abstract

In the current literature, in order to be able to detect a single observation as an outlier observation, this observation is represented by a dummy variable and the dummy variable is checked for statistical significance. For an observation to be an outlier observation, the thesis of significant t-statistics of dummy variable is used. This paper proves using a theoretic proof for simple regression model that this thesis is wrong and refutes this thesis using a counterexample. The example derived for this paper illustrates that an outlier observation detected by robust regression methods cannot be detected by the t-statistics of dummy variable. In addition, the effect of adding a dummy variable to regression on important regression statistics is investigated.

Suggested Citation

  • Arzdar KIRACI, 2011. "Kukla Degiskenlerin T Istatistigi ile Aykiri Gozlemler Tespit Edilemez," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 15(1), pages 1-14, November.
    • Handle: RePEc:ist:ancoec:v:15:y:2011:i:1:p:1-14
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    File URL: http://eidergisi.istanbul.edu.tr/sayi15/iueis15m1.pdf
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    More about this item

    Keywords

    Robust Regression; t-statistics; dummy variable; outlier; refute the thesis; simple regression model; detection problem; example;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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