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dc.contributor.advisorBurnett, Thomas D.
dc.contributor.authorJones, Robert William Germany
dc.dateSeptember 1971
dc.date.accessioned2012-11-13T23:23:43Z
dc.date.available2012-11-13T23:23:43Z
dc.date.issued1971-09
dc.identifier.urihttp://hdl.handle.net/10945/15681
dc.description.abstractThe purpose of this thesis is to determine the power relationship, through computer simulation, between the parametric ANOV and non-parametric Wilson tests under controlled conditions of error non-normality. Data is simulated using the 12 cell factorial ANOV model with three levels of factor A, four levels of factor B, and six observations per cell. Interaction is characterized such that its effect is proportional to the effect of factor A with the constant of proportionality related to factor B. Non-normality of the error term is characterized in three distribution types: skewed, leptokurtic (peaked), and platykurtic (flat). Four degrees of the three error distribution types are utilized, each related to the Pearson family of frequency curves. Three thousand-seven hundred sets of data are generated for each degree of error type. Power is then estimated directly for both the ANOV F tests and Wilson Chi-square tests for main effects and interaction. Comparison is then made between corresponding tests showing the effect of error non-normality on the power of each.
dc.description.urihttp://archive.org/details/theeffectoferror1094515681
dc.language.isoen_US
dc.publisherMonterey, California ; Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
dc.titleThe effect of error non-normality on the power of parametric and non-parametric ANOV tests.en_US
dc.typeThesisen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentOperations Research and Administrative Sciences
dc.subject.authoranalysis of variance (ANOV)en_US
dc.subject.authorWilson testen_US
dc.subject.authorpoweren_US
dc.subject.authorsimulationen_US
dc.subject.authorerror distributionen_US
dc.subject.authorinteractionen_US
dc.subject.authornon-normalityen_US
dc.description.serviceLieutenant Colonel, United States Marine Corps
etd.thesisdegree.nameM.S. in Operations Researchen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineOperations Researchen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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