Categorical data analysis in experimental biology

Bo Xu, Xuyan Feng, Rebecca D. Burdine

Research output: Contribution to journalReview article

15 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)3-11
Number of pages9
JournalDevelopmental biology
Volume348
Issue number1
DOIs
StatePublished - Dec 1 2010

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Developmental Biology
  • Cell Biology

Keywords

  • Categorical data
  • Chi-square
  • Confidence interval
  • Statistical significance
  • Ternary diagram

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