Statistics for Immunologists. (2nd August 2018)

• Record Type: Journal Article
• Authors: Skinner, Jeff
• Editors: Coligan, John E.; Bierer, Barbara E.; Margulies, David H.; Shevach, Ethan M.; Strober, Warren
• Is Part Of: Current protocols in immunology. Volume 122(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-08-02
• Subjects: Bayesian -- cross‐validation -- data mining -- design of experiments -- generalized linear model -- graphs -- high throughput -- immunology -- nonlinear -- nonparametric -- parametric -- R project -- regression -- statistics -- survival resampling; Immunology -- Laboratory manuals; Medical protocols; Immunologic Techniques; Medical protocols; Immunology; Laboratory manuals; Reference works; 571.96028
• DOI: 10.1002/cpim.54
• Languages: English
• ISSNs: 1934-3671

Abstract

Abstract: 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. © 2018 by John Wiley & Sons, Inc.