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Bay Arinze – Journal of Statistics and Data Science Education, 2023
Data Analytics has grown dramatically in importance and in the level of business deployments in recent years. It is used across most functional areas and applications, some of the latter including market campaigns, detecting fraud, determining credit, identifying assembly line defects, health services and many others. Indeed, the realm of…
Descriptors: Data Analysis, Elections, Simulation, Statistics Education
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Per Nilsson; Andreas Eckert – Mathematical Thinking and Learning: An International Journal, 2024
This study contributes to the call for influencing practice by increasing attention to how learning environments can be designed to support learning in statistical inference. We report on a design experiment in secondary school (students 14-16 years old), that resulted in a set of lessons with the learning goal of teaching students how to apply…
Descriptors: Mathematics Instruction, Teaching Methods, Hypothesis Testing, Secondary School Students
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Mario Alberto de la Puente Pacheco; Carlos Mario de Oro Aguado; Elkyn Lugo Arias; Heidy Rico; Diana Cifuentes; Merlys Tafur – Interactive Learning Environments, 2023
This Article analyses the effectiveness of Simulation-Based Learning Model ASEAN Meeting in enhancing critical thinking skills and academic performance compared to the conventional teaching method among 216 International Relations undergraduate students on the north coast of Colombia. A t-student test, Welch test, and the Kendall Tau correlation…
Descriptors: Critical Thinking, Models, Inquiry, Active Learning
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Lübke, Karsten; Gehrke, Matthias; Horst, Jörg; Szepannek, Gero – Journal of Statistics Education, 2020
Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…
Descriptors: Inferences, Simulation, Attribution Theory, Teaching Methods
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Dinov, Ivo D.; Palanimalai, Selvam; Khare, Ashwini; Christou, Nicolas – Teaching Statistics: An International Journal for Teachers, 2018
Statistical inference involves drawing scientifically-based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. We designed, implemented, and validated a new portable randomization-based statistical inference infrastructure (http://socr.umich.edu/HTML5/Resampling_Webapp) that blends…
Descriptors: Statistical Inference, Sampling, Simulation, Computer Oriented Programs
LuPone, Kathleen A. – ProQuest LLC, 2017
Results from previous studies indicated nursing students needed to further develop critical thinking (CT) especially with respect to employing it in their clinical reasoning. Thus, the study was conducted to support development of students' CT in the areas of inference subskills that could be applied as they engaged in clinical reasoning during…
Descriptors: Critical Thinking, Undergraduate Students, Nursing Students, Inferences
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Tintle, Nathan; Clark, Jake; Fischer, Karen; Chance, Beth; Cobb, George; Roy, Soma; Swanson, Todd; VanderStoep, Jill – Journal of Statistics Education, 2018
The recent simulation-based inference (SBI) movement in algebra-based introductory statistics courses (Stat 101) has provided preliminary evidence of improved student conceptual understanding and retention. However, little is known about whether these positive effects are preferentially distributed across types of students entering the course. We…
Descriptors: Statistics, College Mathematics, College Preparation, Mathematical Concepts
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Strayer, Jeremy; Matuszewski, Amber – Mathematics Teacher, 2016
In this article, Strayer and Matuszewski present a six-phase strategy that teachers can use to help students develop a conceptual understanding of inferential hypothesis testing through simulation. As Strayer and Matuszewski discuss the strategy, they describe each phase in general, explain how they implemented the phase while teaching their…
Descriptors: Mathematics Instruction, Teaching Methods, Hypothesis Testing, Simulation
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Lee, Hollylynne S.; Doerr, Helen M.; Tran, Dung; Lovett, Jennifer N. – Statistics Education Research Journal, 2016
Repeated sampling approaches to inference that rely on simulations have recently gained prominence in statistics education, and probabilistic concepts are at the core of this approach. In this approach, learners need to develop a mapping among the problem situation, a physical enactment, computer representations, and the underlying randomization…
Descriptors: Probability, Inferences, Statistics, Teaching Methods
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Koparan, Timur; Yilmaz, Gül Kaleli – Universal Journal of Educational Research, 2015
The effect of simulation-based probability teaching on the prospective teachers' inference skills has been examined with this research. In line with this purpose, it has been aimed to examine the design, implementation and efficiency of a learning environment for experimental probability. Activities were built on modeling, simulation and the…
Descriptors: Foreign Countries, Simulation, Preservice Teachers, Inferences
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Larwin, Karen H.; Larwin, David A. – Journal of Education for Business, 2011
Bootstrapping methods and random distribution methods are increasingly recommended as better approaches for teaching students about statistical inference in introductory-level statistics courses. The authors examined the effect of teaching undergraduate business statistics students using random distribution and bootstrapping simulations. It is the…
Descriptors: Experimental Groups, Control Groups, Research Design, Grade Point Average
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Jonassen, David H.; Ionas, Ioan Gelu – Educational Technology Research and Development, 2008
Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…
Descriptors: Cognitive Processes, Inferences, Thinking Skills, Causal Models
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Wood, Michael – Journal of Statistics Education, 2005
This article explores the uses of a simulation model (the two bucket story)--implemented by a stand-alone computer program, or an Excel workbook (both on the web)--that can be used for deriving bootstrap confidence intervals, and simulating various probability distributions. The strengths of the model are its generality, the fact that it provides…
Descriptors: Intervals, Computer Software, Robustness (Statistics), Probability
National Council of Teachers of Mathematics, 2006
The 2006 NCTM Sixty-eighth Yearbook focuses on students' and teachers' learning in statistics centered on a set of activities. Topics include the relation between mathematics and statistics, the development and enrichment of mathematical concepts through the use of statistics, and a discussion of the research related to teaching and learning…
Descriptors: Yearbooks, Probability, Inferences, Educational Technology
Peters, Richard – 1987
Students must be actively involved in the process of learning for it to have personal meaning and importance in their lives. Teachers must also become critical thinkers, creative individuals, and decision makers in order to create more challenging learning environments. Teachers need to blend structure and spontaneity into meaningful learning…
Descriptors: Citizenship Education, Cognitive Processes, Convergent Thinking, Creative Teaching