Statistics Reform: Practitioner’s Perspective

It is widely believed that one of the main causes of the replication crisis in scientific research is some of the most commonly used statistical methods, such as null hypothesis significance testing (NHST). This has prompted many scientists to call for statistics reform. As a practitioner in hydraulics and measurement science, the author extensively used statistical methods in environmental engineering and hydrological survey projects. The author strongly concurs with the need for statistics reform. This paper offers a practitioner’s perspective on statistics reform. In the author’s view, some statistical methods are good and should withstand statistics reform, while others are flawed and should be abandoned and removed from textbooks and software packages. This paper focuses on two methods derived from the _t_-distribution: the two-sample _t_-test and the _t_-interval method for calculating measurement uncertainty. We demonstrate why both methods should be abandoned. We recommend using advanced estimation statistics in place of the two-sample _t_-test and an unbiased estimation method in place of the _t_-interval method. Two examples are presented to illustrate the recommended approaches.