Statistical Implicative Analysis Theory and Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Gras, Régis (Editor), Suzuki, Einoshin (Editor), Guillet, Fabrice (Editor), Spagnolo, Filippo (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Series: Studies in Computational Intelligence, 127
• Subjects: Engineering.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).; Applications of Mathematics.

Statistical implicative analysis is a data analysis method created by Régis Gras almost thirty years ago which has a significant impact on a variety of areas ranging from pedagogical and psychological research to data mining. Statistical implicative analysis (SIA) provides a framework for evaluating...

Table of Contents:

• Methodology and concepts for SIA
• An overview of the Statistical Implicative Analysis (SIA) development
• CHIC: Cohesive Hierarchical Implicative Classification
• Assessing the interestingness of temporal rules with Sequential Implication Intensity
• Application to concept learning in education, teaching, and didactics
• Student's Algebraic Knowledge Modelling: Algebraic Context as Cause of Student's Actions
• The graphic illusion of high school students
• Implicative networks of student's representations of Physical Activities
• A comparison between the hierarchical clustering of variables, implicative statistical analysis and confirmatory factor analysis
• Implications between learning outcomes in elementary bayesian inference
• Personal Geometrical Working Space: a Didactic and Statistical Approach
• A methodological answer in various application frameworks
• Statistical Implicative Analysis of DNA microarrays
• On the use of Implication Intensity for matching ontologies and textual taxonomies
• Modelling by Statistic in Research of Mathematics Education
• Didactics of Mathematics and Implicative Statistical Analysis
• Using the Statistical Implicative Analysis for Elaborating Behavioral Referentials
• Fictitious Pupils and Implicative Analysis: a Case Study
• Identifying didactic and sociocultural obstacles to conceptualization through Statistical Implicative Analysis
• Extensions to rule interestingness in data mining
• Pitfalls for Categorizations of Objective Interestingness Measures for Rule Discovery
• Inducing and Evaluating Classification Trees with Statistical Implicative Criteria
• On the behavior of the generalizations of the intensity of implication: A data-driven comparative study
• The TVpercent principle for the counterexamples statistic
• User-System Interaction for Redundancy-Free Knowledge Discovery in Data
• Fuzzy Knowledge Discovery Based on Statistical Implication Indexes.