Categorical data analysis in experimental biology.
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.
Xu
Bo
B
Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
Feng
Xuyan
X
Burdine
Rebecca D
RD
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
Stat Med. 1998 Apr 30;17(8):857-72
9595616
Philos Trans R Soc Lond B Biol Sci. 2003 Jan 29;358(1429):223-30
12594930
BMC Genomics. 2006 Feb 08;7:20
16466575
Development. 2009 May;136(10):1621-31
19395640
J Virol. 2006 Sep;80(17):8371-8
16912288
J Cell Biol. 2007 Apr 9;177(1):7-11
17420288
Mol Biol Evol. 2007 Sep;24(9):2029-39
17630280
Development. 2007 Apr;134(8):1605-15
17360770