This paper presents the results of a research study related to the Navy and Marine Corps Intranet (NMCI). This study used MANOVA and one-way ANOVA, including post hoc tests, to analyze data sets corresponding to service level agreement metrics for over 300 Navy sites. Within the NMCI network, factors size, server farm, Network Operations Center (NOC), area, region, and group are affecting the performance metrics as defined in the service level agreements (SLA). Each one of the factors is statistically disparate for at least one SLA. Checks for normality indicate nonnormal behavior for most data sets. The results, conclusions, and recommendations have been provided to Navy service level managers to improve the system.
","abstract_html":"<p>This paper presents the results of a research study related to the Navy and Marine Corps Intranet (NMCI). This study used MANOVA and one-way ANOVA, including post hoc tests, to analyze data sets corresponding to service level agreement metrics for over 300 Navy sites. Within the NMCI network, factors size, server farm, Network Operations Center (NOC), area, region, and group are affecting the performance metrics as defined in the service level agreements (SLA). Each one of the factors is statistically disparate for at least one SLA. Checks for normality indicate nonnormal behavior for most data sets. The results, conclusions, and recommendations have been provided to Navy service level managers to improve the system.</p>","abstract_has_math":false,"creators":["Quintana, Jamie Lee"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Open Access Thesis","degree_discipline":"Engineering Technology","degree_department":null,"school":null,"contributors":["Tracy Tillman, PhD, Chair","Robert Chapman, PhD","Hiral Shah"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-04-01T08:00:00Z","date_published":"2006-04-01T08:00:00Z","updated_at":"2026-07-24T02:16:24Z","subjects":["Multivariate analysis Data processing","Information technology Management","Management information systems","Intranets (Computer networks)","United States. Navy Management","Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/65","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Tracy Tillman, PhD, Chair","Robert Chapman, PhD","Hiral Shah"]},{"key":"dc:creator","label":"Author","values":["Quintana, Jamie Lee"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Technology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Multivariate analysis Data processing","Information technology Management","Management information systems","Intranets (Computer networks)","United States. Navy Management","Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/65"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This paper presents the results of a research study related to the Navy and Marine Corps Intranet (NMCI). This study used MANOVA and one-way ANOVA, including post hoc tests, to analyze data sets corresponding to service level agreement metrics for over 300 Navy sites. Within the NMCI network, factors size, server farm, Network Operations Center (NOC), area, region, and group are affecting the performance metrics as defined in the service level agreements (SLA). Each one of the factors is statistically disparate for at least one SLA. Checks for normality indicate nonnormal behavior for most data sets. The results, conclusions, and recommendations have been provided to Navy service level managers to improve the system.
"]},{"key":"dc:title","label":"Title","values":["A causal comparative factorial analysis of factors affecting service level agreements in a U.S. Navy enterprise information systems network"]}]}],"canonical_facts":{"dc:contributor":["Tracy Tillman, PhD, Chair","Robert Chapman, PhD","Hiral Shah"],"dc:creator":["Quintana, Jamie Lee"],"dc:description.abstract":["This paper presents the results of a research study related to the Navy and Marine Corps Intranet (NMCI). This study used MANOVA and one-way ANOVA, including post hoc tests, to analyze data sets corresponding to service level agreement metrics for over 300 Navy sites. Within the NMCI network, factors size, server farm, Network Operations Center (NOC), area, region, and group are affecting the performance metrics as defined in the service level agreements (SLA). Each one of the factors is statistically disparate for at least one SLA. Checks for normality indicate nonnormal behavior for most data sets. The results, conclusions, and recommendations have been provided to Navy service level managers to improve the system.
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