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Journal of Statistics and Data Science Education Volume 29, 2021 - Issue 3
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Articles

Student-Developed Shiny Applications for Teaching Statistics

Sabrina Luxin WangDepartment of Statistics, Penn State University, University Park, PA
,
Anna Yinqi ZhangDepartment of Statistics, Penn State University, University Park, PA
,
Samuel MesserDepartment of Statistics, Penn State University, University Park, PA
,
Andrew WiesnerDepartment of Statistics, Penn State University, University Park, PA
&
Dennis K. PearlDepartment of Statistics, Penn State University, University Park, PACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1981-1826
ORCID Icon
Pages 218-227 | Published online: 26 Nov 2021

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Read on this site (4)

Yuanting Lu. (2023) Web-Based Applets for Facilitating Simulations and Generating Randomized Datasets for Teaching Statistics. Journal of Statistics and Data Science Education 31:3, pages 264-272.
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Qing Wang & Xizhen Cai. (2023) Active-Learning Class Activities and Shiny Applications for Teaching Support Vector Classifiers. Journal of Statistics and Data Science Education 0:0, pages 1-15.
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Andrew J. Sage, Yang Liu & Joe Sato. (2022) From Black Box to Shining Spotlight: Using Random Forest Prediction Intervals to Illuminate the Impact of Assumptions in Linear Regression. The American Statistician 76:4, pages 414-429.
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Mine Dogucu & Mine Çetinkaya-Rundel. (2022) Tools and Recommendations for Reproducible Teaching. Journal of Statistics and Data Science Education 30:3, pages 251-260.
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Articles from other publishers (2)

Stratos Moschidis, Athanasios C. Thanopoulos & Christina Karamichalakou. (2023) Developing and hosting web data apps in R programming for official statistics. Statistical Journal of the IAOS, pages 1-11.
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Álvaro Toledo San Martín & Inés Vicencio Pardo. (2023) Aplicaciones interactivas basadas en el paquete SHINY/R para explicar conceptos estadísticos. HUMAN REVIEW. International Humanities Review / Revista Internacional de Humanidades 17:4, pages 1-15.
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