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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
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
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
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
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
McLean, Jeffrey A.; Doerr, Helen M. – North American Chapter of the International Group for the Psychology of Mathematics Education, 2015
This study focuses on the development of four tertiary introductory statistics students' informal inferential reasoning while engaging in data driven repeated sampling and resampling activities. Through the use of hands-on manipulatives and simulations with technology, the participants constructed empirical sampling distributions in order to…
Descriptors: College Mathematics, College Students, Statistics, Statistical Inference
Buchanan, Taylor L.; Lohse, Keith R. – Measurement in Physical Education and Exercise Science, 2016
We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…
Descriptors: Researchers, Attitudes, Statistical Significance, Bias
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Ramler, Ivan P.; Chapman, Jessica L. – Journal of Statistics Education, 2011
In this article we describe a semester-long project, based on the popular video game series Guitar Hero, designed to introduce upper-level undergraduate statistics students to statistical research. Some of the goals of this project are to help students develop statistical thinking that allows them to approach and answer open-ended research…
Descriptors: Video Games, Hypothesis Testing, Programming, Statistics
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
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

Derry, Sharon; And Others – Teaching of Psychology, 1995
Maintains that literacy and informed decision making in an uncertain world require the ability to reason statistically. Describes a course designed to help students use statistical concepts as tools for social reasoning within simulations of real-world problems. Describes four types of instructional activities used. (CFR)
Descriptors: Cognitive Processes, Course Content, Course Descriptions, Critical Thinking