title: Categorical data analysis in experimental biology.
abstract: The 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 cannot 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.
authors.affiliation: Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
authors.forename: Bo
authors.initials: B
authors.lastname: Xu
authors.forename: Xuyan
authors.initials: X
authors.lastname: Feng
authors.forename: Rebecca D
authors.initials: RD
authors.lastname: Burdine
mesh_terms: D000818:Animals; D001695:Biology / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D003626:Data Display; D003627:Data Interpretation, Statistical; D015509:Developmental Biology / Q000706:statistics & numerical data; D014773:Virology / Q000706:statistics & numerical data
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