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Creators/Authors contains: "McGaughey, Karen"

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  1. ; ; ; ; ; (, Journal of Statistics and Data Science Education)
    “Simulation-based inference” is often considered a pedagogical strategy for helping students develop inferential reasoning, for example, giving them a visual and concrete reference for deciding whether the observed statistic is unlikely to happen by chance alone when the null hypothesis is true. In this article, we highlight for teachers some implications of different simulation strategies when analyzing two variables. In particular, does it matter whether the simulation models random sampling or random assignment? We present examples from comparing two means and simple linear regression, highlighting the impact on the standard deviation of the null distribution. We also highlight some possible extensions that simulation-based inference easily allows. Supplementary materials for this article are available online. 
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  2. ; ; (, Bridging the Gap: Empowering and Educating Today's Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
    Learning standards for biology courses have called for increasing statistics content. Little is known, however, about biology students’ attitudes towards statistics content and what students actually learn about statistics in these courses. This study aims to uncover changes in attitudes and content knowledge in statistics for students in biology courses. One hundred thirty-four introductory biology students across five different instructors participated in a pre-post study of statistical thinking and attitudes toward statistics. Students performed better on the statistics conceptual inventory at the end of a biology course compared to the beginning. Student attitudes showed no change. These preliminary results suggest the potential importance for laying a conceptual foundation in statistics prior to taking biology courses with little formal statistical instruction. 
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