Frank Konietschke, Charité Berlin
Small data: A big data problem
Small sample sizes occur frequently and especially in preclinical research. Most statisticalmethods are only valid if sample sizes are large and thus, investigating the methods' behavior whensamples are small is tempting. It turns out, that few statistical methods are as reliable as throwing a coinwhen samples are small. In this talk, we propose few improvements using resampling and permutationmethods. In particular, we will answer the question "When and how do permutation methods work?". Realdata sets illustrates the application of the proposed mean based and purely nonparametric rank-basedmethods.