Categorical data analysis in experimental biology

Bo Xu, Xuyan Feng, Rebecca D. Burdine

Research output: Contribution to journalReview articlepeer-review

16 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

Fingerprint Dive into the research topics of 'Categorical data analysis in experimental biology'. Together they form a unique fingerprint.

Cite this