 Simpson’s Paradox is not limited to categorical data: it can occur for cardinal data as well and show up in standard models for quantitative analysis. A famous example is the analysis of SAT scores—the results of college admission tests—in the United States as a function of the high school grade point average (GPA) of students. The data are given in  Table 4:  the overall SAT average rises from 1992 to 2002, but for each GPA group (A+/A/…), SAT averages are falling. This phenomenon is, however, very natural. As soon as there is a bit of grade inflation at high schools, each group loses their best students to the next higher group, lowering the SAT average per group. But this is of course consistent with the overall SAT average remaining equal, or even rising from 501 to 516, like in our dataset. A conclusion from the stratified data that “students are getting more stupid” would be mistaken. Since societal developments such as grade inflation affect both the grade distribution and the SAT scores, one should not condition on the GPA of a student when studying SAT scores over time (compare the back-door criterion from  Section 3.4).[11]