Significance testing, with appropriate multiple testing correction, is currently the most convenient method for summarizing the evidence for association between a disease and a genetic variant.

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Statistical significance is a critical concept in data analysis and research. In essence, it’s a measure that allows researchers to assess whether the results of an experiment or study are due to ...

Statistical testing and lower bounds in distributed estimation constitute a rapidly evolving area that addresses both the design of robust tests for assessing data properties across networked systems ...

A test of statistical significance addresses the question, How likely is a result, assuming the null hypotheses to be true. Randomness, a central assumption underlying commonly used tests of ...

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have ...

Given the highly infectious nature of the COVID pathogen, tests for the virus had to be quick, reliable and safe. The test ...

This is a preview. Log in through your library . Abstract A nonparametric statistical test of the performance of ordinations is adapted and extended from the work of Feigin and Cohen (1978). Two ...

The first dimension is the most fundamental: statistical fidelity. It is not enough for synthetic data to look random. It must behave like real data. This means your distributions, cardinalities, and ...