Synonyms for the term "type II error" include the phrases "false negative" or "beta error". Type II error refers to a statistical or hypothesis testing error that occurs when we fail to reject a null hypothesis that is, in fact, false. This typically happens when there is not enough evidence to support the alternative hypothesis. The concept of a false negative highlights the failure to identify a genuine effect or relationship in a study or experiment. "Beta error" is another term used to describe type II errors, emphasizing the risk of accepting false null hypotheses. Understanding these synonyms helps researchers and statisticians comprehend the potential fallibility of their findings.