In 2016, the American Statistical Association1 released an editorial warning against the misuse of statistical significance in interpreting scientific research. Another commentary was recently published in the journal Nature,2 calling for the research community to abandon the concept of statistical significance.
Before being published in Nature,3 the article states it was endorsed by more than 800 statisticians and scientists from around the world. Why are so many researchers concerned about the P-value in statistical analysis?
In 2014, George Cobb, a professor emeritus of mathematics and statistics, posed two questions to members of an American Statistical Association discussion forum.4 In the first question, he asked why colleges and grad schools teach P=0.05, and found this was the value used by the scientific community. In the second question he asked why the scientific community used this particular P-value and found this was what was taught in school.
In other words, it was circular logic that drove the continued belief in an arbitrary value of P=0.05. Additionally, researchers and manufacturers may alter the perception of statistical significance, demonstrating a positive response occurs in an experimental group over the control group simply by using either relative or absolute risk.
However, since many are not statisticians, it’s helpful to first understand the mathematical basis behind P-values, confidence intervals and how absolute and relative risk may be easily manipulated….