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Ernesto Sánchez; Victor Nozair García-Ríos; Francisco Sepúlveda – Educational Studies in Mathematics, 2024
Sampling distributions are fundamental for statistical inference, yet their abstract nature poses challenges for students. This research investigates the development of high school students' conceptions of sampling distribution through informal significance tests with the aid of digital technology. The study focuses on how technological tools…
Descriptors: High School Students, Concept Formation, Thinking Skills, Skill Development
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Sánchez Sánchez, Ernesto; García Rios, Víctor N.; Silvestre Castro, Eleazar; Licea, Guadalupe Carrasco – North American Chapter of the International Group for the Psychology of Mathematics Education, 2020
In this paper, we address the following questions: What misconceptions do high school students exhibit in their first encounter with significance test problems through a repeated sampling approach? Which theory or framework could explain the presence and features of such patterns? With brief prior instruction on the use of Fathom software to…
Descriptors: High School Students, Misconceptions, Statistical Significance, Testing
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Fergusson, Anna; Pfannkuch, Maxine – Journal of Statistics Education, 2020
Informally testing the fit of a probability distribution model is educationally a desirable precursor to formal methods for senior secondary school students. Limited research on how to teach such an informal approach, lack of statistically sound criteria to enable drawing of conclusions, as well as New Zealand assessment requirements led to this…
Descriptors: Foreign Countries, Statistics Education, Probability, Goodness of Fit
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van Dijke-Droogers, Marianne; Drijvers, Paul; Bakker, Arthur – Mathematical Thinking and Learning: An International Journal, 2020
While various studies suggest that informal statistical inference (ISI) can be developed by young students, more research is needed to translate this claim into a well-founded learning trajectory (LT). As a contribution, this paper presents the results of a cycle of design research that focuses on the design, implementation, and evaluation of the…
Descriptors: Statistical Inference, Grade 9, Sampling, Statistical Distributions
Setyani, Geovani Debby; Kristanto, Yosep Dwi – Online Submission, 2020
Drawing inference from data is an important skill for students to understand their everyday life, so that the sampling distribution as a central topic in statistical inference is necessary to be learned by the students. However, little is known about how to teach the topic for high school students, especially in Indonesian context. Therefore, the…
Descriptors: High School Students, Grade 11, Private Schools, Foreign Countries
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Case, Catherine; Jacobbe, Tim – Statistics Education Research Journal, 2018
Although hypothesis testing is ubiquitous in data analysis, research suggests it is commonly misunderstood. Simulation-based inference methods have potential to make student thinking visible, thus providing a valuable lens to analyze developing conceptions about inference. This paper identifies difficulties made visible through simulation-based…
Descriptors: Statistics, Statistical Inference, Logical Thinking, Introductory Courses
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Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
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Zhang, Zhiyong; Lai, Keke; Lu, Zhenqiu; Tong, Xin – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Despite the widespread popularity of growth curve analysis, few studies have investigated robust growth curve models. In this article, the "t" distribution is applied to model heavy-tailed data and contaminated normal data with outliers for growth curve analysis. The derived robust growth curve models are estimated through Bayesian…
Descriptors: Structural Equation Models, Bayesian Statistics, Statistical Inference, Statistical Distributions
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Laumakis, Paul – Mathematics Teacher, 2011
When taking mathematics courses, students will sometimes ask their recurring question, "When will I ever use this in real life?" Educators are often unable to provide a direct connection between what they are teaching in the classroom and a real-life application. However, when such an opportunity does arise, they should seize it and…
Descriptors: Regression (Statistics), Mathematics Instruction, Mathematics, Mathematics Curriculum
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Rossman, Allan J. – Statistics Education Research Journal, 2008
This paper identifies key concepts and issues associated with the reasoning of informal statistical inference. I focus on key ideas of inference that I think all students should learn, including at secondary level as well as tertiary. I argue that a fundamental component of inference is to go beyond the data at hand, and I propose that statistical…
Descriptors: Statistical Inference, Probability, Sampling, Statistical Distributions
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Pfannkuch, Maxine – Statistics Education Research Journal, 2006
Drawing conclusions from the comparison of datasets using informal statistical inference is a challenging task since the nature and type of reasoning expected is not fully understood. In this paper a secondary teacher's reasoning from the comparison of box plot distributions during the teaching of a Year 11 (15-year-old) class is analyzed. From…
Descriptors: Educational Practices, Statistical Inference, Teaching Methods, Secondary School Teachers