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dc.contributor.authorFilipovic, Nicholas
dc.contributor.authorScott, Alison J.
dc.contributor.authorPenlidis, Alexander
dc.date.accessioned2022-04-13 14:22:07 (GMT)
dc.date.available2022-04-13 14:22:07 (GMT)
dc.date.issued2021-01-01
dc.identifier.urihttps://doi.org/10.18260/2-1-370.660-122355
dc.identifier.urihttp://hdl.handle.net/10012/18144
dc.description© 2021 American Society for Engineering Education. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference.en
dc.description.abstractAs future chemical engineers, it is important that students be able to identify and quantify sources of error. A statistical analysis technique that is often overlooked is hierarchical design methodology, which allows for the separation of overall variance into several related components. While hierarchical methodology is relevant to many fields, we have demonstrated that it can be taught through the synthesis and characterization of polymeric materials. Basic statistical concepts are described, along with relevant examples.en
dc.language.isoenen
dc.publisherASEEen
dc.relation.ispartofseriesChemical Engineering Education;
dc.subjectcharacterizationen
dc.subjecthierarchical designen
dc.subjectpolymersen
dc.subjectstatisticsen
dc.titleHierarchical Data Analysis for the Characterization of Polymeric Materials: Linking Measurements and Statistical Methodologyen
dc.typeArticleen
dcterms.bibliographicCitationFilipovic, N., Scott, A. J., & Penlidis, A. (2021). Hierarchical Data Analysis for the Characterization of Polymeric Materials: Linking Measurements and Statistical Methodology. Chemical Engineering Education, 55(1), 11–22. https://doi.org/10.18260/2-1-370.660-122355en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Chemical Engineeringen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


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