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 ...

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 ...

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 ...

Goodness-of-fit testing forms a fundamental pillar in statistical methodology, providing robust tools to assess whether observed data conform to a proposed probability distribution. These tests are ...

As I’ve discussed previously, there are a number of theoretical and practical issues that plague psychological research in terms of statistical testing. On the theoretical end of things, if you ...

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 ...

The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion 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 ...

How many people have the coronavirus in the United States? More than two months into the country’s outbreak, this remains the most important question for its people, schools, hospitals, and businesses ...