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tandfonline.com – A Bayesian Statistics Course for Undergraduates: Bayesian Thinking, Computing, and Research

tandfonline.com har udgivet en rapport under søgningen “Teacher Education Mathematics”: Abstract Abstract We propose a semester-long Bayesian statistics course for undergraduate students with calculus and probability background. We cultivate students’ Bayesian thinking with Bayesian methods applied to real data problems. We leverage modern Bayesian computing techniques not only for implementing Bayesian methods, but also to deepen students’ understanding of the methods. Collaborative case studies further enrich students’ learning and provide experience to solve open-ended applied problems. The course has an emphasis on undergraduate research, where accessible academic journal articles are read, discussed, and critiqued in class. With increased confidence and familiarity, students take the challenge of reading, implementing, and sometimes extending methods in journal articles for their course projects. Supplementary materials for this article are available online. Link til kilde

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tandfonline.com – Spatial Data in Undergraduate Statistics Curriculum

tandfonline.com har udgivet en rapport under søgningen “Teacher Education Mathematics”: Abstract Formulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom. Abstract In this paper we present and discuss the importance and relevance of the inclusion of spatial data analysis as part of the undergraduate statistics curriculum. Given its usefulness and applicability across a range of disciplines, spatial data is a topic that should receive more emphasis within undergraduate statistics curricula. There exist many topical and intriguing spatial data sets from different areas of research that can bring fruitful discussions into the classroom including the environment, medicine, and political science.… Continue Reading

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tandfonline.com – Computational Skills for Multivariable Thinking in Introductory Statistics

tandfonline.com har udgivet en rapport under søgningen “Teacher Education Mathematics”: Abstract Formulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom. Abstract Since the publishing of Nolan and Temple Lang’s “Computing in the Statistics Curriculum” in 2010, the American Statistical Association issued new recommendations in the revised GAISE College report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop multivariable thinking when they analyze real data in the context of investigating research questions of interest, which typically involve complex relationships between many variables. Proficiency in a statistical programming language facilitates the development of… Continue Reading

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tandfonline.com – Comparing Student Performance in a Graduate-Level Introductory Biostatistics Course Using an Online versus a Traditional in-Person Learning Environment

tandfonline.com har udgivet en rapport under søgningen “Teacher Education Mathematics”: Abstract Formulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom. Abstract Our study compared the performance of students enrolled in a graduate-level introductory biostatistics course in an online versus a traditional in-person learning environment at a school of public health in the United States. We extracted data for students enrolled in the course online and in person from 2013 to 2018. We compared average quiz and final exam scores between students in the two learning environments adjusting for demographic characteristics and prior academic performance using linear mixed models. Data… Continue Reading