Null hypothesis significance testing (NHST) is arguably the most widely used<br>approach to hypothesis evaluation among behavioral and social scientists. It is also<br>very controversial. A major concern expressed by critics is that such testing is<br>misunderstood by many of those who use it. Several other objections to its use have<br>also been raised. In this article the author reviews and comments on the claimed<br>misunderstandings as well as on other criticisms of the approach, and he notes<br>arguments that have been advanced in support of NHST. Alternatives and supplements<br>to NHST are considered, as are several related recommendations regarding<br>the interpretation of experimental data. The concluding opinion is that NHST is<br>easily misunderstood and misused but that when applied with good judgment it can<br>be an effective aid to the interpretation of experimental data.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education