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Marek Arendarczyk; Tomasz J. Kozubowski; Anna K. Panorska – Journal of Statistics and Data Science Education, 2023
We provide tools for identification and exploration of data with very large variability having power law tails. Such data describe extreme features of processes such as fire losses, flood, drought, financial gain/loss, hurricanes, population of cities, among others. Prediction and quantification of extreme events are at the forefront of the…
Descriptors: Natural Disasters, Probability, Regression (Statistics), Statistical Analysis
Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
Rehder, Bob – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Two experiments tested how the "functional form" of the causal relations that link features of categories affects category-based inferences. Whereas "independent causes" can each bring about an effect by themselves, "conjunctive causes" all need to be present for an effect to occur. The causal model view of category…
Descriptors: Role, Classification, Causal Models, Inferences
Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2016
We extend to the longitudinal setting a latent class approach that was recently introduced by Lanza, Coffman, and Xu to estimate the causal effect of a treatment. The proposed approach enables an evaluation of multiple treatment effects on subpopulations of individuals from a dynamic perspective, as it relies on a latent Markov (LM) model that is…
Descriptors: Causal Models, Markov Processes, Longitudinal Studies, Probability
Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric – Cognitive Science, 2012
The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…
Descriptors: Statistical Inference, Probability, Correlation, Causal Models
Fernbach, Philip M.; Erb, Christopher D. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
The authors propose and test a causal model theory of reasoning about conditional arguments with causal content. According to the theory, the acceptability of modus ponens (MP) and affirming the consequent (AC) reflect the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Acceptability…
Descriptors: Causal Models, Logical Thinking, Statistical Analysis, Validity
Holyoak, Keith J.; Lee, Hee Seung; Lu, Hongjing – Journal of Experimental Psychology: General, 2010
A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source…
Descriptors: Inferences, Logical Thinking, Bayesian Statistics, Causal Models
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers