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Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
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Ken Frank; Guan Saw; Qinyun Lin; Ran Xu; Joshua Rosenberg; Spiro Maroulis; Bret Staudt Willet – Grantee Submission, 2025
This is a practical guide for applying the Impact Threshold for a Confounding Variable and the Robustness of Inference to Replacement using the konfound packages in Stata and R as well as the R-shiny app. It includes motivation worked examples, and tutorials.
Descriptors: Robustness (Statistics), Statistical Inference, Programming Languages, Computer Software
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Temesgen Samuel; Hsiu-Ling Chen; Abebayehu Yohannes – Journal of Computer Assisted Learning, 2025
Background: As highly interactive hands-on learning tools, robots can inspire new generations of mathematics students. However, to date, no comprehensive systematic reviews have been conducted on robot-assisted mathematics education from K-12 through higher education. Hence, it is important to explore the research evidence of robot-assisted…
Descriptors: Mathematics Instruction, Robotics, Technology Uses in Education, Elementary Secondary Education