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Chance, Beth; Tintle, Nathan; Reynolds, Shea; Patel, Ajay; Chan, Katherine; Leader, Sean – Statistics Education Research Journal, 2022
Using simulation-based inference (SBI), such as randomization tests, as the primary vehicle for introducing students to the logic and scope of statistical inference has been advocated with the potential of improving student understanding of statistical inference and the statistical investigative process. Moving beyond the individual class…
Descriptors: Mathematics Curriculum, Simulation, Student Characteristics, Prior Learning
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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
Karabatsos, George; Walker, Stephen G. – Society for Research on Educational Effectiveness, 2011
Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…
Descriptors: Bayesian Statistics, Regression (Statistics), Nonparametric Statistics, Statistical Inference