Implications of data-analysis models for careers guidance

Data-analysis models for careers guidance have been mostly of the regression type, operating to transform trait assessments into predictions of career adjustments. If understanding of self and life-space is a prerequisite to decision-making and planning, models of the correlation type - which transform trait distributions of populations into knowledge of the antecedents of variance in careers phenomena - may need to take precedence in guidance programmes. Models of the two types have some guidance implications in common, but each type of model also has some special implications, which are discussed. It is argued that studying correlation models for career development data in the context of a sequential, structured guidance curriculum can provide young people with scientific attitudes and skills which will make them ready for personal predictions, decisions, and planning.