 Understanding the paradox is essential for drawing the proper conclusions from statistical data. To give a recent example involving the paradox (Kügelgen, Gresele, &amp; Schölkopf [see  Other Internet Resources]),  early data revealed that the case fatality rate for Covid-19 was higher in Italy than in China overall. Yet within every age group the fatality rate was higher in China than in Italy. One thus appears to get opposite conclusions about the comparative severity of the virus in the countries depending on whether one compares the whole populations or the age-partitioned populations. Having a proper analysis of what is going on is such cases is thus crucial for using statistics to inform policy.