This tutorial will first discuss the replication crisis in empirical science. This term was coined to describe recent significant failures to replicate empirical findings, in a number of fields, including medicine and psychology. In many cases, over 50% of previously reported results could not be replicated. This fact has shaken the foundations of these fields: Can empirical results really be believed? Should, for example, medical decisions really be based on empirical research? How many psychological findings can we believe? After describing the crisis, the tutorial will revisit enough of the basics of empirical science to explain the origins of the replication crisis. The key issue is that hypothesis testing, which in empirical science is used to establish truth, is the result of a probabilistic process. However, the human mind is wired to reason absolutely: Humans have a difficult time understanding probabilistic reasoning*. The tutorial will discuss some of the ways that funding agencies, such as the US National Institutes of Health (NIH), have responded to the replication crisis, by, for example, funding replication studies, and requiring that grant recipients publicly post anonymized data. Other professional organizations, including IEEE, have recently begun efforts to enhance the replicability of published research. Finally, the tutorial will consider how the Virtual Environments community might respond to the replication crisis. In particular, in our community the reviewing process often considers work that involves systems, architectures, or algorithms. In these cases, the reasoning behind the correctness of the results is usually absolute. Therefore, the standard for accepting papers is that the finding exhibits novelty—to some degree, the result should be surprising. However, this standard does not work for empirical studies (which, typically, involve human experimental subjects). Because empirical reasoning is probabilistic, important results need to be replicated, sometimes multiple times, and by different laboratories. As the replications mount, the field is justified in embracing increasing belief in the results. In other words, consider a field that, in order to accept a paper reporting empirical results, always requires surprise: This is a field that will not progress in empirical knowledge. The tutorial will end with a call for the community to be more accepting of replication studies. In addition, the tutorial will consider whether actions taken by other fields, in response to the replication crisis, might also be recommendable for the Virtual Environments community.