Comparison between Conventional and Fuzzy Hypotheses Test Results for Parameter Treatment Effect for Heart Patients
In the traditional hypotheses test, hypotheses are crisp. In this paper, we consider the hypotheses test for unknown mean in normal populations with fuzzy data when the standard deviation of the population is known. This paper aims to distinguish various parameter effects on clinical Heart Patients...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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Institute of Electrical and Electronics Engineers Inc.
2020
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097546130&doi=10.1109%2fICCI51257.2020.9247733&partnerID=40&md5=354d3023e1c1df9e062d2524f98abc9b http://eprints.utp.edu.my/29854/ |
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| Summary: | In the traditional hypotheses test, hypotheses are crisp. In this paper, we consider the hypotheses test for unknown mean in normal populations with fuzzy data when the standard deviation of the population is known. This paper aims to distinguish various parameter effects on clinical Heart Patients with Two-way Anova, and in this fuzzy test, we will make a fuzzy decision for rejection or acceptance null hypothesis on various parameters of clinical data of Heart Patients with Fuzzy p-value and compared the results with the conventional hypothesis test results. These results will be a benchmark for new patients (same characteristics as the old patients) to treat them in a better way. © 2020 IEEE. |
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