The data scientist’s goal is to simultaneously reduce bias and variance as much as possible in order to obtain as accurate model as is feasible. However, there is a tradeoff to be made when selecting ...

System-wide measurements of gene expression by DNA microarray and, more recently, RNA-sequencing strategies have become de facto tools of modern biology and have led to deep understanding of ...

Interpreting 'omics data often involves statistical analysis of large numbers of loci such as genes, binding sites or single-nucleotide polymorphisms (SNPs). Although the data set as a whole may be ...

Discover how sample size neglect impacts statistical conclusions and learn to avoid this cognitive bias studied by renowned experts like Tversky and Kahneman.