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Kurt, Gamze – Statistics Education Research Journal, 2023
This paper reports the statistical and probabilistic reasoning of young children in terms of randomness, variability, and data representations in the context of informal inferential reasoning (IIR). Using the IIR approach, a task was designed and conducted one-on-one with 28 children aged 5 to 6 years old, in a case study setting. The researcher…
Descriptors: Young Children, Childrens Attitudes, Cognitive Processes, Abstract Reasoning
Robinson, Alexander; Keller, L. Robin; del Campo, Cristina – Decision Sciences Journal of Innovative Education, 2022
COVID-19 pandemic policies requiring disease testing provide a rich context to build insights on true positives versus false positives. Our main contribution to the pedagogy of data analytics and statistics is to propose a method for teaching updating of probabilities using Bayes' rule reasoning to build understanding that true positives and false…
Descriptors: Data, Error Patterns, Visual Aids, Graphs
English, Lyn D. – Statistics Education Research Journal, 2023
This article reports on a study in which third-grade students (8-9 years) were given a degree of agency in conducting chance experiments and representing the outcomes. Students chose their own samples of 12 coloured counters, ensuring all colours were represented. They predicted the outcomes of item selection, tested their predictions, explained…
Descriptors: Grade 3, Elementary School Students, Color, Probability
Koparan, Timur; Rodríguez-Alveal, Francisco – Journal of Pedagogical Research, 2022
Solving real-life problems through mathematical modeling is one of the aims of modern mathematics curricula. For this reason, prospective mathematics teachers need to acquire modeling skills and use these skills in learning environments in terms of creating rich learning environments. With this study, it is aimed to examine the reflections of…
Descriptors: Probability, Thinking Skills, Preservice Teachers, Graphs
Duxbury, Scott W. – Sociological Methods & Research, 2023
This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…
Descriptors: Graphs, Scaling, Research Problems, Models
Lu, Yonggang; Zheng, Qiujie; Quinn, Daniel – Journal of Statistics and Data Science Education, 2023
We present an instructional approach to teaching causal inference using Bayesian networks and "do"-Calculus, which requires less prerequisite knowledge of statistics than existing approaches and can be consistently implemented in beginner to advanced levels courses. Moreover, this approach aims to address the central question in causal…
Descriptors: Bayesian Statistics, Learning Motivation, Calculus, Advanced Courses
Jungck, John R. – PRIMUS, 2022
Finite Mathematics has become an enormously rich and productive area of contemporary mathematical biology. Fortunately, educators have developed educational modules based upon many of the models that have used Finite Mathematics in mathematical biology research. A sufficient variety of computer modules that employ graph theory (phylogenetic trees,…
Descriptors: Mathematics Instruction, Teaching Methods, Mathematical Models, Learning Modules

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