AppTweak's Simon Thillay explains why app marketing teams should prioritize business outcomes over statistical significance.

“The problem was hiding in plain sight,” François explains. “What was masquerading as an asset in the form of Statistical Significance was, in reality, stifling innovation.

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

A new publication by two University of Cincinnati researchers contends that adjusting how researchers approach their statistical analysis has the potential to change the lives of children and ...

For example, sniffing camphor, taking ivermectin, or oleandrin were not "practical" treatments for the COVID-19 virus. In other words, they did not work, and those who promoted them as cures or ...

A Primer on Statistical Significance To prevail in a toxic tort action, the plaintiff must show both general causation and specific causation. Under Federal Rule of Evidence 702, an expert can ...

Research in social and biomedical science often uses a statistical method known as null hypothesis testing to determine whether results are “statistically significant.” A P value less than 0. ...

The concept of statistical significance predated Gosset, but prior statisticians worked in the regime of large sample sizes. To appreciate why this distinction matters, we need to understand how ...

Statistical significance of clustering (SigClust) is a recently developed cluster evaluation tool for high-dimensional low sample size (HDLSS) data. An important component of the SigClust approach is ...