Categorical data analysis in experimental biology |
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Authors: | Bo Xu |
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Affiliation: | Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA |
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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. |
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Keywords: | CI, confidence interval CL, confidence level SE, standard error |
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