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dc.contributor.authorShim, Mi Yeon
dc.date.accessioned2014-03-04T19:00:17Z
dc.date.available2014-03-04T19:00:17Z
dc.date.issued2010-12
dc.identifier.othershim_mi-yeon_201012_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/shim_mi-yeon_201012_ms
dc.identifier.urihttp://hdl.handle.net/10724/27007
dc.description.abstractMany agricultural scientists doing technical experiments analyze data themselves. It allows them to save high analyzing cost. However, it may cause a problem. Since scientists often have their preferred way to analyze data, they usually use the same statistical method even though the experiments are conducted with different designs. If the statistical method which they use is not appropriate for the data, the corresponding results will not be correct. Statistical analyses are important methods for interpreting results of agricultural experiments. Statistical analyses also need to be clearly communicated so that readers can properly interpret the results of experiments with poultry. Different statistical models and programming statements may lead to quite different conclusions.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectAnalysis of Variance
dc.subjectRegression
dc.subjectInteraction
dc.subjectStatistical Analysis
dc.subjectQualitative and quantitative factors
dc.subjectA × linear B
dc.subjectlinear A × linear B contrasts
dc.titleThe interpretation of experiments with poultry
dc.typeThesis
dc.description.degreeMS
dc.description.departmentStatistics
dc.description.majorStatistics
dc.description.advisorLynne Billard
dc.description.committeeLynne Billard
dc.description.committeeGene Pesti
dc.description.committeeAbhyuday Mandal


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