With the 2020 Joint Statistical Meetings in the rear view mirror and the fall semester under way, we wanted to take some time to reflect on our first virtual conference of this scale. While we were pleased to see the progress in the field of statistics education, we left feeling a little disappointed in the experience of the virtual conference overall. Below Adam and guest contributor Ann Brearley (University of Minnesota) share some of their favorite takeaways from the conference, which include topics like social justice, consulting and collaborating, teaching math stats courses, and approaches for talking about more difficult concepts…Continue reading “JSM 2020 Takeaways”
As outlined by Cobb (2007), most introductory statistics books teach classical hypothesis tests as
- formulating null and alternative hypotheses,
- calculating a test statistic from the observed data,
- comparing the test statistic to a reference (null) distribution, and
- deriving a p-value on which a conclusion is based.
This is still true for the first course, even after the 2016 GAISE guidelines were adapted to include normal- and simulation-based methods. Further, most textbooks attempt to carefully talk through the logic of hypothesis testing, perhaps showing a static example of hypothetical samples that go into the reference distribution. Applets, such as StatKey and the Rossman Chance ISI applets, take this a step further, allowing students to gradually create these simulated reference distributions in an effort to build student intuition and understanding. While these are fantastic tools, I have found that many students still struggle to understand what the purpose of a reference distribution is and the overarching logic of testing. To remedy this, I have been using visual inference to introduce statistical testing, where “plots take on the role of test statistics, and human cognition the role of statistical tests” (Buja et al., 2009). In this process, I continually encourage students to apply Sesame Street logic: which one of these is not like the other? By using this alternative approach that focuses on visual displays over numerical summaries, I have been pleased with the improvement in student understanding, so I thought I would share the idea with the community.Continue reading “Visual Inference: Using Sesame Street Logic to Introduce Key Statistical Ideas”