Multiple hypothesis testing is an important part of many high-throughput data analysis workflows. A common objective is to maximize the number of discoveries while controlling the expected fraction of ...
It is of fundamental interest in statistics to test the significance of a set of covariates. For example, in genomewide association studies, a joint null hypothesis of no genetic effect is tested for ...
The pursuit of science is designed to search for significance in a maze of data. At least, that’s how it’s supposed to work. To support or refute a hypothesis, the goal is to establish statistical ...
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