JMM 2014

Two weeks ago I traveled to Baltimore to the Joint Mathematics Meetings. These meetings are very much like the Joint Statistics Meetings except for mathematicians. “Now, um, usually I don’t do this but uh….Go head’ on and break em off wit a lil’ preview of the remix….” (Kelly, 2003).

The JMM are a great place to educate and work with mathematics teachers at the collegiate level who are teaching introductory statistics courses. One group that is quite active in this community is the Statistics Education Special Interest Group of the Mathematical Association of America (SIGMAA). If you are a member of the MAA, let me put in a plug to join this SIGMAA. Each year they sponsor at least one contributed paper session and often several minicourses.

This year, aside from the perennial Teaching introductory statistics (for instructors new to teaching intro stats minicourse, the SIGMAA also endorsed two minicourses aimed at using randomization/bootstrapping in the introductory course, CATALST: Introductory statistics using randomization and bootstrap methods and Using randomization methods to build conceptual understanding of statistical inference. Both mini courses were well attended and will likely be offered again next January.


Nicola during the CATALST minicourse.

The SIGMAA also sponsored a Contributed Paper Session entitled, Data, Modeling, and Computing in the Introductory Statistics Course. The marathon session, running from 1:00pm–6:00pm, was very well attended and included 15 presentations.


Nick Horton gives the paper, Big Data in the Intro Stats Class: Use of the Airline Delays Dataset to Expose Students to a Real-World, Complex Dataset by himself, Ben Baumer, and Hadley Wickham.

One of my favorite things at JMM is attending the SIGMAA Stat-Ed Business Meeting. This took place immediately following the CPS, so we were able to capitalize on inviting many of the attendees to join us. After eating what might have been the best spread of food I have encountered at one of these meetings, we had our meeting.

The SIGMAA presents two awards during these meetings.

The Dex Whittinghill Award is presented to the first author of the paper that receives the highest evaluations during the CPS session from the previous JMM. This year, it was presented to Kari Lock-Morgan of Duke University (who was unable to be there, but sent her heartfelt thanks via her parents).

The Robert V. Hogg Award for excellence in teaching introductory statistics was presented to Johanna Hardin of Pomona College. Johanna’s colleague, Gizem Karaali, gave a heartwarming talk when presenting Johanna the award.


Scott Albers, SIGMAA chair, congratulates Johanna Hardin on winning the Robert V. Hogg Award


Gizem Karaali reads a heartwarming note from the Johanna’s colleagues.



Kelly, R. (2003). Ignition (remix). On Chocolate factory. Chicago: Jive, Sony.

Conditional probabilities and kitties

I was at the vet yesterday, and just like with any doctor’s visit experience, there was a bit of waiting around — time for re-reading all the posters in the room.


And this is what caught my eye on the information sheet about feline heartworm (I’ll spare you the images):


The question asks: “My cat is indoor only. Is it still at risk?”

The way I read it, this question is asking about the risk of an indoor only cat being heartworm positive. To answer this question we would want to know P(heartworm positive | indoor only).

However the answer says: “A recent study found that 27% of heartworm positive cats were identified as exclusively indoor by their owners”, which is P(indoor only | heartworm positive) = 0.27.

Sure, this gives us some information, but it doesn’t actually answer the original question. The original question is asking about the reverse of this conditional probability.

When we talk about Bayes’ theorem in my class and work through examples about sensitivity and specificity of medical tests, I always tell my students that doctors are actually pretty bad at these, looks like I’ll need to add vets to my list too!