Learn the NumPy trick for generating synthetic data that actually behaves like real data.

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.

The books Lies, Damn Lies, and Statistics (Wheeler, 1976) and Damned Lies and Statistics (Best, 2001) have raised questions about whether statistics can be trusted. A number of educated people today, ...

The advent of technologies to probe DNA copy number genome-wide has led to rapid progress in the understanding of how segments of the genome can vary in copy number between individuals 1,2. In ...

This is a preview. Log in through your library . Abstract In recent years various structures have been proposed for estimating intensity of consumer preference in consumer surveys. Empirical studies ...

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 ...

In Part 1 of this ChipCenter feature article, we looked back in time and traced some events that led to the adoption of statistical process control (SPC). However, the implementation of a robust SPC ...