Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward
By Nicholas J. Horton. 2015
51 citations recorded by the source corpus.
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.
Subfields: Artificial Intelligence, Modeling and Simulation, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/0fe0e30d37386454c8fd91e95966cb68697dd034
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Citations in the corpus
- Teaching the Next Generation of Statistics Students to “Think With Data”: Special Issue on Statistics and the Undergraduate Curriculum (2015, background): “But there are challenges as well as opportunities in this new world of data (Horton 2015; Ridgway 2015a).”
- Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report 2016 (2016, background): “Horton (2015) writes that “the lack of application for simple multivariable methods is a major limitation of too many of our courses” (p. 141).”