Education, Éducation, Sciences de l'éducation, Educational sciences, Recherche en éducation, Educational research, Méthodologie, Methodology, Méthodes statistiques, informatique, Statistical methods, computer science, Science sociale, Social Science, and Statistique
In the data analysis of social science studies, the researcher often summarizes similar characteristics or responses relating to his subjects into a single index. A popular index is the arithmetic average. The advantage of this index is that it is easy to calculate, it has intuitive meaning, and it offers fairness, i.e., it attributes the same weight to each of its components. However, this index is not very efficient in terms of its ability to represent the original data - especially where many original variables are involved. This paper attempts to substantiate this statement, and proposes the first axis of the Principal Components Analysis as an index, which, besides its capacity to summarize, is far more efficient than the average. Didactic and real examples are presented, comparing this index with the average.
Hebrew Univ., Rehovot (Israel). Faculty of Agriculture and Wolf, S.
Plant physiology and biochemistry, Mathematical and statistical methods, TOMATOES, PLANT DEVELOPMENTAL STAGES, ENVIRONMENTAL CONDITIONS, NON-OPTIMIZING METHODS/ ISRAEL, COMPUTERS, TOMATE, STADE DE DEVELOPPEMENT VEGETAL, CONDITION DE MILIEU, METHODE NON OPTIMISANTE / ISRAEL, ORDINATEUR, ETAPAS DE DESARROLLO DE LA PLANTA, CONDICIONES AMBIENTALES, SIMULACION / ISRAEL, and COMPUTADOR