South Australian Branch June Meeting – Teaching Statistics to Undergraduates

The June meeting of the SA Branch attracted a large audience (a full house!) on a cold Adelaide Winter night. It was a delight to have Mary Barnes share her rich knowledge and experience, and her rather humorous presenting style provided a highly engaging talk on a somewhat “daunting” topic.

Mary is a biostatistics lecturer in the Flinders Centre for Epidemiology and Biostatistics, Flinders University. She was once a metallurgist, but she became frustrated in this profession because she couldn’t understand when she had made a real change in steelwork production lines. After studying statistics part time she became a statistician, and now has 30 years’ research experience as a statistician. Mary worked at CSIRO for 25 years in multidisciplinary research analysing a vast range of data from industry and medicine, for example data relating to: outcomes from medical procedures, nutrition, agriculture, environmental monitoring and quality management. In her previous roles Mary has enjoyed training adults, and she is excited how her current role provides the opportunity to inspire university students to enjoy learning and applying statistics to the medical sciences.

In her talk, Mary introduced the latest ideas on teaching statistics to undergraduate students at tertiary level. The discussion included student engagement, quizzes during lectures, tailoring teaching through the use of pre and post testing to identify areas of focus, and flipped classrooms (allowing for more class time discussion and focus on areas of weakness). She shared the top five effective principles/approaches derived from cognitive theory on statistical education advocated by Lovett and Greenhouse:

  1. Students learn best what they practice and perform on their own
  2. Knowledge tends to be specific to the context in which it is learned
  3. Learning is more efficient when students receive real-time feedback on errors
  4. Learning involves integrating new knowledge with existing knowledge
  5. Learning becomes less efficient as the mental load students must carry increases

Mary provided an example of a simple way to reduce the mental load for students. In her class she encourages students use their own datasets, and use datasets related to their area of study in order to avoid unnecessary mental load in trying to figure out the meaning of variable names.  She also discussed the merits and limitations of the many online resources available for both lecturers and students in statistical teaching and learning. Following are some of the website details.


Resources Website
Ted talks
Nicola Petty’s blogs from NZ
Chris Wild NZ
iNZight: A data analysis system with a particularly short learning curve
Rossman/Chance Applet Collection
Shiny from R studio
Statistics How To
StatSoft has freely provided the Electronic Statistics Textbook
American Statistical association
Dancing Statistical Concepts
E-books by G. David Garson


By Rosie Meng


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