DETERMINING OUT-OF-CONTROL VARIABLE(S) IN A MULTIVARIATE QUALITY CONTROL CHART FOR INDIVIDUAL OBSERVATIONS

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dc.contributor.authorAGOG, NATHAN SAMUEL
dc.date.accessioned2015-03-05T10:38:08Z
dc.date.available2015-03-05T10:38:08Z
dc.date.issued2014-08
dc.descriptionA THESIS SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES, AHMADU BELLO UNIVERSITY, ZARIA NIGERIA IN PARTIAL FULFILMENT FOR THE AWARD OF MASTER OF SCIENCE (M.Sc) DEGREE IN STATISTICS, DEPARTMENT OF MATHEMATICS AHMADU BELLO UNIVERSITY, ZARIA NIGERIA. AUGUST, 2014en_US
dc.description.abstractThe decomposition of the Hotelling’s T2 statistic into orthogonal components is considered to be one of the most effective methods for detecting variable(s) responsible for an out-of-control signal. In this work, an extension of the T2 decomposition from three variables (p=3) to four (p=4) variables, where the number of decompositions increased from 3! = 6 to 4! = 24 and the decomposition terms also increased from 18 to 96 terms having 32 distinct terms were provided. These distinct terms are the ones that were examined for possible contribution to the T2 signal. A dataset obtained from an Indomie company in Northern Nigeria was used to assess the validity of constructed model by demonstrating the invariance property of the Hotelling’s T2 statistic. The model was also used to identify the variable(s) that significantly contribute to an out-of-control signal. By comparing the critical values with the corresponding T2 values, we were able to detect variation between the four (4) variables in their mean and also their variancecovariance structure.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/6103
dc.language.isoenen_US
dc.subjectOUT-OF-CONTROLen_US
dc.subjectVARIABLEen_US
dc.subjectMULTIVARIATE QUALITYen_US
dc.subjectCONTROL CHARTen_US
dc.subjectINDIVIDUAL OBSERVATIONSen_US
dc.titleDETERMINING OUT-OF-CONTROL VARIABLE(S) IN A MULTIVARIATE QUALITY CONTROL CHART FOR INDIVIDUAL OBSERVATIONSen_US
dc.typeThesisen_US
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