The CAUSE Cartoon Caption Contest for April is now taking entries
The Consortium for the Advancement of Undergraduate Statistics Education is happy to
announce our eleventh Cartoon Caption Contest. Each month a cartoon, drawn by British
cartoonist John Landers, will be posted for you and your students to suggest statistical
captions. (note the cartoons are post on the 2nd day of each month)
The next cartoon and the entry rules for the contest ending April 1 are at
https://www.causeweb.org/cause/caption-contest/april/2017/submissions
The best captions will be posted on CAUSEweb and the winner(s) will receive their choice
of a coffee mug or t-shirt imprinted with the cartoon or free registration to eCOTS 2018.
Enjoy.
March Results: We had 36 submissions for the March caption contest that featured a cartoon
showing two professionals in front of a giant spinner with various variable names (age;
shoe size; tobacco; fever; and vitamin C) - the spinner appears to be landing on
"age". The March caption contest had two co-winners. The first was “Let's
see what The Wheel of Non-Causal Relationships comes up with this month for strongest
predictor of disease X,” written by Michael Posner from Villanova University and chosen
for it’s theme about model building and the inferences that might be drawn in
observational studies. The co-winning caption: “I'll go tell the patient it's her
age making her sick today . Good thing I don't have to explain that it's her big
feet!“ was written by Michele Balik-Meisner, a student at North Carolina State University
was selected for its humorous nature and the ability to use the cartoon to discuss how
evidence should be examined in light of the associated science (e.g. there might be
science behind a causal relationship between some of the variables on the spinner and an
illness – but certainly not with shoe size).
Honorable mentions this month go to Mickey Dunlap from University of Georgia for his
caption “No no no! You randomize AFTER you select your research topic!”, to Larry Lesser
from The University of Texas at El Paso for his caption “This isn't what I meant by
'random variable!” and to Greg Snow from Brigham Young University for his caption “We
find this method of finding "significant" predictors to be quicker than using
stepwise regression and it is even slightly more reproducible.” (useful in a course for
majors that covers the caveats in using a model building procedure like stepwise
regression).
Thanks to everyone who submitted a caption and congratulations to our Winners!