#### Send to
jQuery(document).ready( function () {
jQuery("#send_to_menu input[type='radio']").click( function () {
var selectedValue = jQuery(this).val().toLowerCase();
var selectedDiv = jQuery("#send_to_menu div." + selectedValue);
if(selectedDiv.is(":hidden")){
jQuery("#send_to_menu div.submenu:visible").slideUp();
selectedDiv.slideDown();
}
});
});
jQuery("#sendto").bind("ncbipopperclose", function(){
jQuery("#send_to_menu div.submenu:visible").css("display","none");
jQuery("#send_to_menu input[type='radio']:checked").attr("checked",false);
});

# Statistics for Immunologists

### 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.

- PMID:
- 30400720
- PMCID:
- PMC6223127
- DOI:
- 10.1002/cpim.54

- [Indexed for MEDLINE]