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Categorical data analysis in experimental biology

Author(s): Xu, Bo; Feng, Xuyan; Burdine, Rebecca D.

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dc.contributor.authorXu, Bo-
dc.contributor.authorFeng, Xuyan-
dc.contributor.authorBurdine, Rebecca D.-
dc.date.accessioned2020-02-20T23:34:03Z-
dc.date.available2020-02-20T23:34:03Z-
dc.date.issued2010-12en_US
dc.identifier.citationXu, Bo, Feng, Xuyan, Burdine, Rebecca D. (2010). Categorical data analysis in experimental biology. Developmental Biology, 348 (1), 3 - 11. doi:10.1016/j.ydbio.2010.08.018en_US
dc.identifier.issn0012-1606-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr14f4p-
dc.description.abstractThe categorical data set is an important data class in experimental biology and contains data separable into several mutually exclusive categories. Unlike measurement of a continuous variable, categorical data can not be analyzed with methods such as the student’s t-test. Thus, these data require a different method of analysis to aid in interpretation. In this article, we will review issues related to categorical data, such as how to plot them in a graph, how to integrate results from different experiments, how to calculate the error bar/region, and how to perform significance tests. In addition, we illustrate analysis of categorical data using experimental results from developmental biology and virology studies.en_US
dc.format.extent3 - 11en_US
dc.language.isoen_USen_US
dc.relation.ispartofDevelopmental Biologyen_US
dc.rightsAuthor's manuscripten_US
dc.titleCategorical data analysis in experimental biologyen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1016/j.ydbio.2010.08.018-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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