This cartoon was created by Martha Pienkowski, a student at the University of Toronto at Mississauga and won an honorable mention in the 2019 A-mu-sing Contest. The cartoon reviews a comparison about the assumptions and use among various hypothesis test methods. The cartoon compares the z-test, the t-test, and nonparametric alternatives like the sign test and the Wilcoxon test in paired and unpaired situations.
This cartoon was created Jona Gjevori and Ahmed Salam, when they were undergraduate students at the University of Toronto at Mississauga. The cartoon won an honorable mention in the 2019 A-mu-sing Contest and is designed to humorously facilitate the discussion of issues of generalizing to the population of interest (e.g. in generalizing results in animal students to assume validity for humans without further testing).
This cartoon was created by Jashandeep Nijjar and Ajandan Nandakumar, students from the University of Toronto at Mississauga and took second place in the 2019 A-mu-sing Contest. The cartoon is designed to help in teaching about a type of bias in sample surveys. It depicts a situation when a satisfaction survey about a restaurant is given out on the grand opening night when they are giving out free food and thus, spuriously gives highly positive results about the restaurants quality.
This cartoon was created by Austin Boyd from University of Tennessee and took first place in the cartoon category of the 2019 A-mu-sing Contest. The cartoon provides a humorous way to facilitate conversation about the multiple comparisons caveat (that the chance of getting at least one significant result grows with the number of things being tested) and the large sample caveat (that it is more likely to see small p-values with smaller effect sizes when you have a larger sample size).
This cartoon was drawn in the style of Randall Munroe's xkcd web comic by Tubba Babar, a student from University of Toronto Mississauga and won second place in the cartoon category of the 2019 A-mu-sing Contest. The cartoon can be used in discussing the difference between correlation and causation and the fact that observational relationships can often not distinguish between "A implies B" and "B implies A". The graphic in the cartoon shows two things rising in prevalence over the same period of time. Thus, it can be used to discuss how many things have changed in the same direction over time, forming a vast number of spurious correlations.
This cartoon is a meme created by Amy Finnegan from Duke University that received an honorable mention in the 2019 A-mu-sing Contest. The meme can be used to facilitate class discussions of the difference between an estimate being precise versus being accurate. The dog represents an estimate and the dog bed represents the target (parameter). When the dog is curled up would indicate high precision and when the dog is spread out that would represent low precision. When the dog is in the bed that would indicate accuracy and when the dog is not in the bed, that would indicate lack of accuracy. (Note: in classes where the language of “reliability” is used instead of “precision” the meme can be renamed Accuracy vs Reliability and the representations in discussions should then be changed accordingly.)
This lyric written, performed, and recorded in 2018 by Larry Lesser (The University of Texas at El Paso) won honorable mention in the 2019 A-mu-sing contest. The song helps launch learning about permutations by showing how many ways n distinct objects can be ordered for the first non-trivial case (n = 3), modelling the systematic strategy of listing orderings in alphabetical order to make sure none are missed. (Before using the song, students can be asked for their prediction – many will say 3 or 9 instead of 6. After using the song, students can be asked to find the answer for n = 4, which is just small enough to generate by hand.) The song also introduces vocabulary (“order”, “permuted”, “sort”) commonly used in this context.
This lyric was written and recorded/sung by Larry Lesser from The University of Texas at El Paso in 2017 to the tune of the Miley Cyrus hit “Wrecking Ball.” The song won honorable mention in the 2019 A-mu-sing contest and is designed to be a vehicle to discuss common instances of expected value as a benchmark for making real-world decisions in one’s life. In particular, students should be aware that most people sometimes choose to buy something (an insurance policy, a warranty, a lottery ticket, etc.) whose expected value is negative, but that is still outweighed by other considerations. The second verse refers to an episode of “Deal or No Deal” (Season 4, Episode 7) that NBC aired on October 22, 2008.
This lyric, written by Larry Lesser (The University of Texas at El Paso) and Michael Posner (Villanova University) and recorded/sung by Lesser in 2019, won fourth place in the 2019 A-mu-sing contest. The song may be sung to the tune of "She Blinded Me With Science" by Thomas Dolby and is designed to introduce some key terms and concepts in data science.
This poem was written by students Gill Marjorie Onate and Muzaffar Bhatti from University of Toronto Mississauga and was given an honorable mention in the poetry category of the 2019 A-mu-sing competition. The poem is designed to aid discussions about when a non parametric test might be used instead of a normal throw test and the difference between paired and unpaired data.