The article "The Insignificance of Statistical Significance Testing" by Douglas H. Johnson critically examines the use of statistical hypothesis testing in scientific research, particularly in wildlife management. Johnson argues that while statistical hypothesis tests are widely used, they often add little value to research and can even confuse interpretations of data. He discusses the arbitrariness of P-values, the fallacy of concluding that the null hypothesis is true based on a small P-value, and the distinction between statistical and biological significance. Johnson contrasts statistical hypothesis testing, which often tests hypotheses known to be false, with scientific hypothesis testing, which examines credible hypotheses about natural phenomena. He suggests more meaningful alternatives such as estimation and confidence intervals, decision theory, and Bayesian approaches. Johnson emphasizes the importance of replication in science and the need for editors and referees to ensure that statistical methods are appropriately applied. The article concludes by advocating for the use of more appropriate statistical tools in wildlife research to enhance the reliability and relevance of findings.The article "The Insignificance of Statistical Significance Testing" by Douglas H. Johnson critically examines the use of statistical hypothesis testing in scientific research, particularly in wildlife management. Johnson argues that while statistical hypothesis tests are widely used, they often add little value to research and can even confuse interpretations of data. He discusses the arbitrariness of P-values, the fallacy of concluding that the null hypothesis is true based on a small P-value, and the distinction between statistical and biological significance. Johnson contrasts statistical hypothesis testing, which often tests hypotheses known to be false, with scientific hypothesis testing, which examines credible hypotheses about natural phenomena. He suggests more meaningful alternatives such as estimation and confidence intervals, decision theory, and Bayesian approaches. Johnson emphasizes the importance of replication in science and the need for editors and referees to ensure that statistical methods are appropriately applied. The article concludes by advocating for the use of more appropriate statistical tools in wildlife research to enhance the reliability and relevance of findings.