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172 – Bayesian Computations: Challenges, Solutions, and Implementations in Medical Product Development
Statistical Education: Steadfast or Stubborn
Milo Schield
Augsburg College
This paper claims (1) that the introductory statistics course is essentially the same in content as it was 50 years ago, (2) that statistical education has ignored many - if not most - of the content changes proposed by leaders in statistical education, and (3) that the introductory statistics course is essentially a math-stat (research-methods) course. One explanation is that statistics education is being steadfast in upholding random variation as the central idea and ultimate goal of the introductory course. Examples of how context (confounding, assumptions and bias) can influence statistical significance are shown using confidence intervals as a test of statistical significance. Statistics educators seem unwilling to adopt this into introductory statistics. An alternate explanation is that statistics educators want the introductory course to be maintained as a research methods course dedicated to upholding the purity and rigor of deductive mathematics. If so, then any attempt to introduce context may require that statistical educators actively support a separate course in statistical literacy.