Some Comments on the Robustness of Student t Procedures

Abstract Many business and engineering courses stress the use of confidence interval and hypothesis testing procedures based on the Student t distribution. However, students are often unaware of the underlying assumptions that govern these procedures and of the consequences of misapplying them. In this exegetic account, we discuss the concept of robustness by exploring violations of the Student t assumptions and the effects of those violations on the resulting inferences. We also discuss the use of randomization methods as possible alternative methods. Our goal is to familiarize readers with the underpinnings of the t procedures, to summarize their use in practice, and to offer words of caution as to when they should not be used.