In this ASI13 symposium, we aim to highlight original contributions that implement the theory of Statistical Implicative Analysis (S.I.A.) as a methodological framework for studying the roles and effects of contexts and resources in various fields, including education, training, and conditions of efficiency.

The following recurring themes will once again be explored:

• Fundamental concepts in SIA: statistical models, types of variables, primary and supplementary variables;
• Ongoing developments: various metaphors of SIA, stability of indices, entropic implication intensity; extension to new types of variables, continuous subject space; exception rules; duality of subject space and rule space, metric structure and topology of the subject space induced by contribution or typicality, vector analysis, SIA and paracoherent logic;
• Critical comparison of approaches, models, representations, and results of SIA with those from other data analysis methods (Galois lattices, Bayesian networks, decision trees, factor analyses, etc.);
• Use of the CHIC software and the RCHIC package, current and expected developments;
• Specificities of SIA training: use of the CHIC software and RCHIC package, interpretation of graphical representations (implicative graph; cohesive hierarchy tree);
• Applications treated by SIA and in comparison with other methods, in the fields of didactics, educational sciences, psychology, sociology, economics, art history, biology, medicine, archaeology, etc.;
• Graphical and numerical presentations of application results, tools for interpreting these results, respective roles and critiques of the types of variables, and of the selected primary and supplementary variables;
• Interest of SIA in analyzing the results of international assessments (PISA, TIMSS, PIRLS, …);
• Didactic issues of SIA