Comparisons can be considered the cornerstone of science, though accurate ones can be notoriously difficult to achieve. In research design, comparisons appear in the context of control groups. When a medication is described as safe and effective, the only way to establish that is through comparisons, including to placebo; a pill that seems to alleviate pain may in fact subjectively do so but is only considered effective if it alleviates pain better than an identical pill without an active ingredient. Outside the rigors of science, comparisons are common in everyday life and on social media. Sometimes they’re accurate, but often they’re deeply flawed and presented in service of some specific advertising, political, or social agenda (for more, see my article “Skepticism and Pseudoexperiments” in the September/October 2020 issue of SI). Flawed comparisons and analogies can be difficult to spot, and I have a particular interest in visual misrepresentations, specifically charts, graphs, and maps that are presented as self-evidently authoritative but are inaccurate or, more insidiously, technically accurate but misleading. In his classic book Envisioning Information, …