Full topic list
This is a session of Topic 4: Statistics education at the post secondary (tertiary) level

(Monday 12th, 11:00-12:30)

A taxonomy of statistics courses



A traditional course of study for undergraduate students specializing in statistics may begin with training in mathematics and probability followed by a theoretical introduction to testing and estimation based firmly in parametric methods. A traditional syllabus for a statistics course for students from other disciplines forgoes the theory, instead offering a series of recipes for data analysis emphasizing parametric methods based on the normal distribution. Consideration of the development of the quantitative skills required for efficient citizens is often relegated to a rarely required course in statistics and society. Does our course organization allow us to adequately train our students?

Papers in this session will address how we organize and classify our statistics course offerings and how this organization should respond to new approaches to data analysis. Issues to be considered include:
  • Should our courses be classified by student? Does the dichotomy of courses for experts and practitioners make sense? Should we introduce our future experts to statistics with a different approach than we use for future practitioners from other disciplines? And do practitioners in biology require a different introduction than practitioners in business or practitioners in other disciplines?
  • Should our courses be classified by method? Does an immersion in data through case studies sufficiently serve our students? Or do we need more structure based on statistical topics? Which of the 1000’s of potential methods should we teach? Should training in statistics be training in a sequence of methods, or development of a broader methodology?
  • Should our courses be classified as theoretical or applied? What statistical theory should be isolated to separate courses in mathematical statistics?


PaperTitlePresenter(s) / Author(s)
4A1Banishing the theory-applications dichotomy from statistics educationLarry Weldon (Canada)
4A2Accommodating specialists and non-specialists in statistics coursesKevin Keen (Canada)
4A3Specialized basic courses for engineering students: a necessity or a nuisance?Lena Zetterqvist (Sweden)