the early years once you control for students backgrounds. But all stu- dents in a bad school, black and white, do lose ground to students in good schools. Perhaps educators and researchers are wrong to be so hung up on the black-white test score gap; the bad-school/good- school gap may be the more salient issue. Consider this fact: the ECLS data reveal that black students in good schools dont lose ground to their white counterparts, and black students in good schools outperform whites in poor schools. So according to these data, a childs school does seem to have a clear impact on his academic progress. Can the same be said for par- enting? Did all those Baby Mozart tapes pay off? What about those   marathon readings of Goodnight Moon? Was the move to the suburbs worthwhile? Do the kids with PTA parents do better than the kids whose parents have never heard of the PTA?       The wide-ranging ECLS data offer a number of compelling correla- tions between a childs personal circumstances and his school perfor- mance. For instance, once all other factors are controlled for, it is clear that students from rural areas tend to do worse than average. Subur- ban children, meanwhile, are in the middle of the curve, while urban children tend to score higher than average. (It may be that cities at- tract a more educated workforce and, therefore, parents with smarter children.) On average, girls test higher than boys, and Asians test higher than whites-although blacks, as we have already established, test similarly to whites from comparable backgrounds and in compa- rable schools. Knowing what you now know about regression analysis, conven- tional wisdom, and the art of parenting, consider the following list of sixteen factors. According to the ECLS data, eight of the factors show a strong correlation-positive or negative-with test scores.