Skinner Jeff
5625 Fishers Lane, Room 4N07C, Rockville, MD 20852
Curr Protoc Immunol. 2018 Aug 2;122(1):54. doi: 10.1002/cpim.54.
Statistical tests and graphs are an important part of any immunological research publication or presentation, but not all immunologists have the statistical expertise to choose the best methods to evaluate and represent their experiments. These protocols provide a brief overview of the statistical methods most relevant to immunology researchers, so they can either analyze their own data or better understand their statistician collaborators. Protocols cover the basics of t‐tests, ANOVA, nonparametric tests, linear and nonlinear regression models, categorical response models, statistical design of experiments, and advanced methods like re‐sampling tests, Bayesian statistics, and methods for high‐throughput ‐omics data. Each topic receives a brief overview of the theory and usage, followed by brief instructions and code examples for R software. These protocols should be useful to biologists who are learning statistics for the first time and biologists who would like a refresher on basic statistical methods.
统计测试和图表是任何免疫学研究出版物或展示的重要组成部分,但并非所有免疫学家都具备统计学专业知识来选择评估和展示其实验的最佳方法。这些方案简要概述了与免疫学研究人员最相关的统计方法,以便他们能够自行分析数据或更好地理解与其合作的统计学家。方案涵盖了t检验、方差分析、非参数检验、线性和非线性回归模型、分类响应模型、实验的统计设计等基础知识,以及重抽样检验、贝叶斯统计和高通量组学数据方法等高级方法。每个主题都对理论和用法进行了简要概述,随后是R软件的简要说明和代码示例。这些方案对于初次学习统计学的生物学家以及希望复习基本统计方法的生物学家应该是有用的。