{"title":"More than Formulas -- Integrity, Communication, Computing and Reproducibility in Statistics Education","authors":"Eva Furrer, Annina Cincera, Reinhard Furrer","doi":"arxiv-2407.08835","DOIUrl":null,"url":null,"abstract":"This paper introduces a novel course design in the Master Program in\nBiostatistics at the University of Zurich that integrates computing skills,\neffective communication, reproducibility, and scientific integrity within one\ncourse. Utilizing a flipped classroom model, the course aims to equip students\nwith the necessary competencies to handle real-world data analysis challenges\nand effective statistical practice in general. The curriculum includes\npractical tools such as version control with Git, dynamic reporting, unit\ntesting and containerization to foster reproducibility, and integrity in\nstatistical practice. Feedback gathered from both staff and students\npost-implementation indicates that the course significantly enhances student\nreadiness for professional and academic environments, demonstrating the\neffectiveness of this educational approach.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"25 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Other Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.08835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces a novel course design in the Master Program in
Biostatistics at the University of Zurich that integrates computing skills,
effective communication, reproducibility, and scientific integrity within one
course. Utilizing a flipped classroom model, the course aims to equip students
with the necessary competencies to handle real-world data analysis challenges
and effective statistical practice in general. The curriculum includes
practical tools such as version control with Git, dynamic reporting, unit
testing and containerization to foster reproducibility, and integrity in
statistical practice. Feedback gathered from both staff and students
post-implementation indicates that the course significantly enhances student
readiness for professional and academic environments, demonstrating the
effectiveness of this educational approach.