the answer may not be very meaningful. Perhaps the number of books in a childs home merely indicates how much money his par- ents make. What we really want to do is measure two children who are alike in every way except one-in this case, the number of books in his home-and see if that one factor makes a difference in his school performance. It should be said that regression analysis is more art than science. (In this regard, it has a great deal in common with parenting itself.) But a skilled practitioner can use it to tell how meaningful a correla- tion is-and maybe even tell whether that correlation does indicate a causal relationship. So what does an analysis of the ECLS data tell us about school- childrens performance? A number of things. The first one concerns the black-white test score gap. It has long been observed that black children, even before they set   foot in a classroom, underperform their white counterparts. More- over, black children didnt measure up even when controlling for a wide array of variables. (To control for a variable is essentially to elim- inate its influence, much as one golfer uses a handicap against an- other. In the case of an academic study such as the ECLS, a researcher might control for any number of disadvantages that one student might carry when measured against the average student.) But this new data set tells a different story. After controlling for just a few variables-including the income and education level of the childs parents and the mothers age at the birth of her first child-the gap between black and white children is virtually eliminated at the time the children enter school. This is an encouraging finding on two fronts. It means that young black children have continued to make gains relative to their white counterparts. It also means that whatever gap remains can be linked to a handful of readily identifiable factors. The data reveal that black