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Loy, Adam – Journal of Statistics and Data Science Education, 2021
In the classroom, we traditionally visualize inferential concepts using static graphics or interactive apps. For example, there is a long history of using apps to visualize sampling distributions. The lineup protocol for visual inference is a recent development in statistical graphics that has created an opportunity to build student understanding.…
Descriptors: Statistics Education, Statistical Inference, Visualization, Visual Aids
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Ziegler, Laura; Garfield, Joan – Statistics Education Research Journal, 2018
The purpose of this study was to develop the Basic Literacy In Statistics (BLIS) assessment for students in an introductory statistics course, at the postsecondary level, that includes, to some extent, simulation-based methods. The definition of statistical literacy used in the development of the assessment was the ability to read, understand, and…
Descriptors: Statistics, Literacy, Introductory Courses, College Students
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Backman, Matthew D.; Delmas, Robert C.; Garfield, Joan – Statistics Education Research Journal, 2017
Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A…
Descriptors: Introductory Courses, Statistics, Mathematics Instruction, Simulation
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Chance, Beth; Wong, Jimmy; Tintle, Nathan – Journal of Statistics Education, 2016
"Simulation-based inference" (e.g., bootstrapping and randomization tests) has been advocated recently with the goal of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Preliminary assessment data have been largely positive. This article describes the analysis of the…
Descriptors: Statistical Inference, Simulation, College Mathematics, Statistics
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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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Mulekar, Madhuri S.; Siegel, Murray H. – Mathematics Teacher, 2009
If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…
Descriptors: Statistical Inference, Statistics, Sample Size, Error of Measurement