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On comparing different tests of the same hypothesis

dc.contributor.authorPerez, Carmen Adelaen
dc.contributor.departmentStatisticsen
dc.date.accessioned2017-01-10T20:34:43Zen
dc.date.available2017-01-10T20:34:43Zen
dc.date.issued1959en
dc.description.abstractThis thesis presents two alternative procedures for comparing standard and quick tests of a null hypothesis H<sub>o</sub>. This comparison is usually made by plotting the power curves of each test for a fixed Type I error. However, the power curves give only an indication of the individual performances of each test and not of the extent to which they agree when applied to the same problem. The procedures discussed in this paper deal with determining this degree of agreement. The first method determines the probability, P, that the quick test leads to a significant result at a level α given that the standard test is just significant at level α. If the standard and quick tests are based on the statistics u₁ and u₂ , respectively, the second approach determines the level of significance corresponding to the expected value of u₂ given that u₁ is just significant at level α. This level of significance is termed the "equivalent Type I error" of the quick test and denoted by γ. Both methods are applied to compare tests of location, dispersion, and the paired t-test with the sign test, all in samples taken from a normal population. In the first two cases, values of P and γ are given for different sample sizes, and in the third case only the “equivalent Type I error" of the sign test is given, P being rather difficult to evaluate.en
dc.description.degreeMaster of Scienceen
dc.format.extent32 leavesen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/10919/74082en
dc.language.isoen_USen
dc.publisherVirginia Polytechnic Instituteen
dc.relation.isformatofOCLC# 26939327en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1959.P474en
dc.subject.lcshCurvesen
dc.subject.lcshStatisticsen
dc.titleOn comparing different tests of the same hypothesisen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Instituteen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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