Hypothesis testing provides organizations with a structured approach to evaluate assumptions using data, reducing reliance on intuition and enhancing decision accuracy. By validating decisions with ...

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.

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 ...

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 ...

High-dimensional statistical testing and covariance analysis constitute a rapidly evolving field that addresses the challenges inherent in analysing datasets where the number of variables often ...

What is the Friedman test? The Friedman test, also sometimes referred to as Friedman’s two-way analysis of variance by ranks, is a non-parametric statistical test used to investigate whether groups 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 ...

Let’s start with a definition of Applied Statistics: Applied Statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an ...

Statistics is to science as steroids are to baseball. Addictive poison. But at least baseball has attempted to remedy the problem. Science remains mostly in denial. True, not all uses of statistics in ...