@article{85211,
  keywords = {Animals, biology, developmental biology, Data Interpretation, Statistical, Virology, Confidence Intervals, Data Display},
  author = {Bo Xu and Xuyan Feng and Rebecca Burdine},
  title = {Categorical data analysis in experimental biology.},
  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{\textquoteright}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. },
  year = {2010},
  journal = {Dev Biol},
  volume = {348},
  pages = {3-11},
  month = {12/2010},
  issn = {1095-564X},
  doi = {10.1016/j.ydbio.2010.08.018},
  language = {eng},
}