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Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward

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  • Nicholas J. Horton

Abstract

The 175th anniversary of the ASA provides an opportunity to look back into the past and peer into the future. What led our forebears to found the association? What commonalities do we still see? What insights might we glean from their experiences and observations? I will use the anniversary as a chance to reflect on where we are now and where we are headed in terms of statistical education amidst the growth of data science. Statistics is the science of learning from data. By fostering more multivariable thinking, building data-related skills, and developing simulation-based problem solving, we can help to ensure that statisticians are fully engaged in data science and the analysis of the abundance of data now available to us.

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  • Nicholas J. Horton, 2015. "Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward," The American Statistician, Taylor & Francis Journals, vol. 69(2), pages 138-145, May.
    • Handle: RePEc:taf:amstat:v:69:y:2015:i:2:p:138-145
    DOI: 10.1080/00031305.2015.1032435
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    References listed on IDEAS

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    1. Horton, Nicholas J. & Brown, Elizabeth R. & Qian, Linjuan, 2004. "Use of R as a Toolbox for Mathematical Statistics Exploration," The American Statistician, American Statistical Association, vol. 58, pages 343-357, November.
    2. Robert Gould, 2010. "Statistics and the Modern Student," International Statistical Review, International Statistical Institute, vol. 78(2), pages 297-315, August.
    3. Lazar, Nicole A. & Reeves, Jaxk & Franklin, Christine, 2011. "A Capstone Course for Undergraduate Statistics Majors," The American Statistician, American Statistical Association, vol. 65(3), pages 183-189.
    4. Robert N. Rodriguez, 2013. "Building the Big Tent for Statistics," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 1-6, March.
    5. Nicholas J. Horton, 2013. "I Hear, I Forget. I Do, I Understand: A Modified Moore-Method Mathematical Statistics Course," The American Statistician, Taylor & Francis Journals, vol. 67(4), pages 219-228, November.
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    Cited by:

    1. Cimpoeru, Smaranda & Roman, Monica, 2018. "Statistical Literacy and Attitudes Towards Statistics of Romanian Undergraduate Students," MPRA Paper 90452, University Library of Munich, Germany, revised 31 Aug 2018.
    2. Constance H. McLaren & Bruce J. McLaren, 2018. "SCOTS: The Searchable Collection of Time Series," INFORMS Transactions on Education, INFORMS, vol. 19(1), pages 12-22, September.
    3. Lisa Dierker & Jane Robertson Evia & Karen Singer-Freeman & Kristin Woods & Janet Zupkus & Alan Arnholt & Elizabeth G Moliski & Natalie Delia Deckard & Kristel Gallagher & Jennifer Rose, 2018. "Project-Based Learning in Introductory Statistics: Comparing Course Experiences and Predicting Positive Outcomes for Students from Diverse Educational Settings," International Journal of Educational Technology and Learning, Scientific Publishing Institute, vol. 3(2), pages 52-64.
    4. Sitsofe Tsagbey & Miguel de Carvalho & Garritt L. Page, 2017. "All Data are Wrong, but Some are Useful? Advocating the Need for Data Auditing," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 231-235, July.

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