Low statistical power undermines the purpose of scientific research; it reduces the chance of detecting a true effect. Perhaps less intuitively, low power also reduces the likelihood that a ...

Modern businesses are awash in data, including operational and financial. Decisions that once relied on management intuition now involve careful analysis of financial statements, spreadsheets and ...

Usually when it comes to writing, mathematics and statistics probably aren’t the first things that come to mind. However, quite the number of us have had to face an instance where a source based on ...

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 ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Robust statistical reasoning is vital in the courtroom, as historical cases have shown. Take, for example, the case of Sally ...

How to use statistical tools for component tolerance analysis. A look at methods such as Monte Carlo and Gaussian distribution. Simulating a dc-dc converter in LTspice to model closed-loop voltage ...

When products start failing, management wants answers. Are they failing because of manufacturing problems? Or is the design to blame? One of the most widely regarded methods for ferreting out the ...