Interpretation of emergent variables on the basis of structure coefficients (zero order correlations between original and emergent variables) is potentially very misleading and should be avoided in favor of interpretation on the basis of scoring coefficients. This is most apparent in multiple regression analysis and its special case, two-group discriminant analysis. Six examples of real and hypothetical data illustrate the pitfalls in interpretation based on structure coefficients. Much of the current commitment to structure-coefficient based interpretations of regression variables and discriminant functions would disappear if researchers would take the additional step of computing a score for each subject on the linear combination of predictors or dependent variables implied by each of the verbal interpretations, and then computing the correlation between each simplified regression variate and "Y" or the "t" for the difference between the two groups with respect to each simplified discriminant function. Four tables are included, and four figures illustrate sample analyses. (SLD)