Cochran’s Q test for analyzing categorical data under uncertainty

Motivation The Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in a dichotomous dataset Description This paper introduces a modified version of Cochran’s Q test using neutrosophic statistics to handle uncer...

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Published in:	Journal of big data Vol. 10; no. 1; pp. 147 - 10
Main Author:	Aslam, Muhammad
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.12.2023 Springer Nature B.V SpringerOpen
Subjects:	Ambiguity Big Data Categorical data analysis Communications Engineering Comparative analysis Comparative studies Computational Science and Engineering Computer Science Consistency Data Data Mining and Knowledge Discovery Database Management Datasets Decision making Determinate Dominance Evaluation Hypothesis testing Information Storage and Retrieval Machinery Mathematical Applications in Computer Science Motivation Networks Neutrosophic logic Nominal measurement Production Simulation Statistical inference Statistical tests Statistics Tests Uncertainty Uncertainty quantification Hypothesis testing Uncertainty quantification Neutrosophic logic Statistical inference Categorical data analysis
ISSN:	2196-1115, 2196-1115
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Abstract	Motivation The Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in a dichotomous dataset Description This paper introduces a modified version of Cochran’s Q test using neutrosophic statistics to handle uncertainty in practical situations. The neutrosophic Cochran’s Q test determines whether the proportions of a specific outcome are consistent across different groups, considering both determinate and indeterminate parts. Results An application of the proposed test is presented using production data to assess the capabilities of machines during different days of the week. The comparative study demonstrates the advantages of the proposed test over the classical Cochran’s Q test, providing insights into the degree of indeterminacy and enhancing decision-making in uncertain scenarios. Conclusion This study introduces a modified version of the Cochran test, utilizing neutrosophic statistics to address uncertainty in practical scenarios. The neutrosophic Cochran’s Q test effectively assesses the consistency of outcome proportions across various groups, accounting for both determinate and indeterminate factors. The application of this novel approach to machine capabilities assessment, based on production data collected over different days of the week, unveils its superiority over the traditional Cochran’s Q test. This superiority is reflected in the insights it offers into the degree of indeterminacy, thereby enhancing decision-making in contexts marked by uncertainty. The simulation study further underscores the critical role of indeterminacy in affecting test statistics and decision outcomes, highlighting the significance of the proposed method in capturing real-world complexities. In essence, the neutrosophic Cochran’s Q test presents a refined and pragmatic tool for addressing the uncertainties inherent in diverse datasets, rendering it invaluable in practical decision-making scenarios.
AbstractList	Abstract Motivation The Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in a dichotomous dataset Description This paper introduces a modified version of Cochran’s Q test using neutrosophic statistics to handle uncertainty in practical situations. The neutrosophic Cochran’s Q test determines whether the proportions of a specific outcome are consistent across different groups, considering both determinate and indeterminate parts. Results An application of the proposed test is presented using production data to assess the capabilities of machines during different days of the week. The comparative study demonstrates the advantages of the proposed test over the classical Cochran’s Q test, providing insights into the degree of indeterminacy and enhancing decision-making in uncertain scenarios. Conclusion This study introduces a modified version of the Cochran test, utilizing neutrosophic statistics to address uncertainty in practical scenarios. The neutrosophic Cochran’s Q test effectively assesses the consistency of outcome proportions across various groups, accounting for both determinate and indeterminate factors. The application of this novel approach to machine capabilities assessment, based on production data collected over different days of the week, unveils its superiority over the traditional Cochran’s Q test. This superiority is reflected in the insights it offers into the degree of indeterminacy, thereby enhancing decision-making in contexts marked by uncertainty. The simulation study further underscores the critical role of indeterminacy in affecting test statistics and decision outcomes, highlighting the significance of the proposed method in capturing real-world complexities. In essence, the neutrosophic Cochran’s Q test presents a refined and pragmatic tool for addressing the uncertainties inherent in diverse datasets, rendering it invaluable in practical decision-making scenarios. Motivation The Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in a dichotomous dataset Description This paper introduces a modified version of Cochran’s Q test using neutrosophic statistics to handle uncertainty in practical situations. The neutrosophic Cochran’s Q test determines whether the proportions of a specific outcome are consistent across different groups, considering both determinate and indeterminate parts. Results An application of the proposed test is presented using production data to assess the capabilities of machines during different days of the week. The comparative study demonstrates the advantages of the proposed test over the classical Cochran’s Q test, providing insights into the degree of indeterminacy and enhancing decision-making in uncertain scenarios. Conclusion This study introduces a modified version of the Cochran test, utilizing neutrosophic statistics to address uncertainty in practical scenarios. The neutrosophic Cochran’s Q test effectively assesses the consistency of outcome proportions across various groups, accounting for both determinate and indeterminate factors. The application of this novel approach to machine capabilities assessment, based on production data collected over different days of the week, unveils its superiority over the traditional Cochran’s Q test. This superiority is reflected in the insights it offers into the degree of indeterminacy, thereby enhancing decision-making in contexts marked by uncertainty. The simulation study further underscores the critical role of indeterminacy in affecting test statistics and decision outcomes, highlighting the significance of the proposed method in capturing real-world complexities. In essence, the neutrosophic Cochran’s Q test presents a refined and pragmatic tool for addressing the uncertainties inherent in diverse datasets, rendering it invaluable in practical decision-making scenarios. MotivationThe Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in a dichotomous datasetDescriptionThis paper introduces a modified version of Cochran’s Q test using neutrosophic statistics to handle uncertainty in practical situations. The neutrosophic Cochran’s Q test determines whether the proportions of a specific outcome are consistent across different groups, considering both determinate and indeterminate parts.ResultsAn application of the proposed test is presented using production data to assess the capabilities of machines during different days of the week. The comparative study demonstrates the advantages of the proposed test over the classical Cochran’s Q test, providing insights into the degree of indeterminacy and enhancing decision-making in uncertain scenarios.ConclusionThis study introduces a modified version of the Cochran test, utilizing neutrosophic statistics to address uncertainty in practical scenarios. The neutrosophic Cochran’s Q test effectively assesses the consistency of outcome proportions across various groups, accounting for both determinate and indeterminate factors. The application of this novel approach to machine capabilities assessment, based on production data collected over different days of the week, unveils its superiority over the traditional Cochran’s Q test. This superiority is reflected in the insights it offers into the degree of indeterminacy, thereby enhancing decision-making in contexts marked by uncertainty. The simulation study further underscores the critical role of indeterminacy in affecting test statistics and decision outcomes, highlighting the significance of the proposed method in capturing real-world complexities. In essence, the neutrosophic Cochran’s Q test presents a refined and pragmatic tool for addressing the uncertainties inherent in diverse datasets, rendering it invaluable in practical decision-making scenarios.
ArticleNumber	147
Author	Aslam, Muhammad
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Cites_doi	10.1016/S0197-2456(03)00026-6 10.3390/sym9100208 10.3390/sym9070123 10.1002/jrsm.1336 10.1007/s11042-023-15313-0 10.2991/jsta.2018.17.2.7 10.1186/s12874-015-0034-x 10.1080/00949655.2022.2108423 10.1186/s40537-023-00700-z 10.1155/2020/7680286 10.1155/2020/2086185 10.14419/ijet.v7i3.18.16662 10.1016/j.jvcir.2023.103776 10.1007/s13042-023-01811-y 10.4135/9781849208499 10.3390/stats5030045 10.5958/2320-3226.2022.00024.8
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Snippet	Motivation The Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in... MotivationThe Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple groups in... Abstract Motivation The Cochran test, also known as Cochran’s Q test, is a statistical procedure used to assess the consistency of proportions across multiple...
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SubjectTerms	Ambiguity Big Data Categorical data analysis Communications Engineering Comparative analysis Comparative studies Computational Science and Engineering Computer Science Consistency Data Data Mining and Knowledge Discovery Database Management Datasets Decision making Determinate Dominance Evaluation Hypothesis testing Information Storage and Retrieval Machinery Mathematical Applications in Computer Science Motivation Networks Neutrosophic logic Nominal measurement Production Simulation Statistical inference Statistical tests Statistics Tests Uncertainty Uncertainty quantification
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Title	Cochran’s Q test for analyzing categorical data under uncertainty
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Volume	10
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