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Possibility Measure of Accepting Statistical Hypothesis

Author

Listed:
  • Jung-Lin Hung

    (Physical Education Office, Kun Shan University, Tainan 710303, Taiwan)

  • Cheng-Che Chen

    (Department of Marketing and Logistics Management, Far East University, Tainan 74448, Taiwan)

  • Chun-Mei Lai

    (Department of Marketing and Logistics Management, Far East University, Tainan 74448, Taiwan)

Abstract

Taking advantage of the possibility of fuzzy test statistic falling in the rejection region, a statistical hypothesis testing approach for fuzzy data is proposed in this study. In contrast to classical statistical testing, which yields a binary decision to reject or to accept a null hypothesis, the proposed approach is to determine the possibility of accepting a null hypothesis (or alternative hypothesis). When data are crisp, the proposed approach reduces to the classical hypothesis testing approach.

Suggested Citation

  • Jung-Lin Hung & Cheng-Che Chen & Chun-Mei Lai, 2020. "Possibility Measure of Accepting Statistical Hypothesis," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:4:p:551-:d:343229
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    References listed on IDEAS

    as
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    3. Abbas Parchami & S. Mahmoud Taheri & Reinhard Viertl & Mashaallah Mashinchi, 2018. "Minimax test for fuzzy hypotheses," Statistical Papers, Springer, vol. 59(4), pages 1623-1648, December.
    4. Abbas Parchami & S. Taheri & Mashaallah Mashinchi, 2010. "Fuzzy p-value in testing fuzzy hypotheses with crisp data," Statistical Papers, Springer, vol. 51(1), pages 209-226, January.
    5. Gholamreza Hesamian & Mohamad Ghasem Akbari, 2017. "Statistical test based on intuitionistic fuzzy hypotheses," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(18), pages 9324-9334, September.
    6. P. Filzmoser & R. Viertl, 2004. "Testing hypotheses with fuzzy data: The fuzzy p-value," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 59(1), pages 21-29, February.
    7. Wu, Chien-Wei, 2009. "Decision-making in testing process performance with fuzzy data," European Journal of Operational Research, Elsevier, vol. 193(2), pages 499-509, March.
    8. Shima Yosefi & Mohsen Arefi & Mohammad Ghasem Akbari, 2016. "A new approach for testing fuzzy hypotheses based on likelihood ratio statistic," Statistical Papers, Springer, vol. 57(3), pages 665-688, September.
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