This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Linear classification functions (LCFs) arise in a predictive discriminant analysis for the purpose of classifying experimental units into criterion groups. The relative contribution of the response variables to classification accuracy may be based on LCF-variable correlations for each group. It is proved that, if the raw response measures are…

Relationships between performance on two preschool administrations of the Metropolitan Readiness Tests (MRT) and Stanford Achievement Test (SAT) scores at age nine were examined for a sample of 732 children. Significant correlations, ranging from .50 to .71, were obtained between readiness scores and SAT scores on reading, spelling and arithmetic.…