Categorical data analysis in experimental biology

被引：24

作者：

Xu, Bo ^{[1
]}

Feng, Xuyan ^{[1
]}

Burdine, Rebecca D. ^{[1
]}

机构：

[1] Princeton Univ, Dept Mol Biol, Princeton, NJ 08544 USA

来源：

DEVELOPMENTAL BIOLOGY | 2010年 / 348卷 / 01期

关键词：

Categorical data; Ternary diagram; Statistical significance; Confidence interval; Chi-square; PROPORTION;

D O I：

10.1016/j.ydbio.2010.08.018

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：3 / 11

页数：9

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