It's really hard to talk about "truth" anywhere, but it's really crucial to both talk about and agree upon the meaning of "truth" in science since, ultimately,

It's really hard to talk about "truth" anywhere, but it's really crucial to both talk about and agree upon the meaning of "truth" in science since, ultimately, that's the goal of the scientific process—the pursuit of the thing. Karl Popper was a major study of this problem and wrote about probably the most common and universally acceptable notion of scientific truth in the mid 1900s. Before then this notion of truth was in practice used, but it may have been difficult to have a clear conversation about it. Worse, without a clear understanding of the properties which give rise to processes with generate "truth" (i.e. the "scientific method" which, even being really generous, is better thought of as a menagerie of related methods) it may have been a little hard to determine whether someone's scientific program would be effective or agreeable. So Popper clarified the notion of "Science as Falsification", of "Truth as what weathers evidence". For Popper, nothing was science unless it was vulnerable to falsification and nothing was true unless it was both science and withstood all attempts to falsify it. This has a major effect on modern statistics. Statistics can be regarded, not entirely incorrectly, as the quantification of the pursuit of truth. It seems to give mechanism to the idea of models relating to evidence and the pruning out of falsified models. It's difficult to ask questions about why statistics is a meaningful tool for scientific pursuits without invoking Popper.