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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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Hahs-Vaughn, Debbie L.; Acquaye, Hannah; Griffith, Matthew D.; Jo, Hang; Matthews, Ken; Acharya, Parul – Journal of Statistics Education, 2017
Statistical literacy refers to understanding fundamental statistical concepts. Assessment of statistical literacy can take the forms of tasks that require students to identify, translate, compute, read, and interpret data. In addition, statistical instruction can take many forms encompassing course delivery format such as face-to-face, hybrid,…
Descriptors: Introductory Courses, Statistics, Graduate Students, Online Courses
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Yamada, Hiroyuki; Bryk, Anthony S. – Community College Review, 2016
Objective: Statway is a community college pathways initiative developed by the Carnegie Foundation for the Advancement of Teaching designed to accelerate students' progress through their developmental math sequence to acquiring college math credit in statistics. Statway is a multifaceted change initiative designed to address the complex problems…
Descriptors: Community Colleges, Program Descriptions, College Credits, Mathematics Instruction
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Aydin, Burak; Leite, Walter L.; Algina, James – Educational and Psychological Measurement, 2016
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
Descriptors: Error of Measurement, Predictor Variables, Randomized Controlled Trials, Experimental Groups
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Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen – American Journal of Evaluation, 2016
Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…
Descriptors: Intervention, Multivariate Analysis, Mixed Methods Research, Models