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, undergraduate 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 restaurant's quality.
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 that 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 poem, with an accompanying video reading of the poem by Michael A. Posner from Villanova University, took first place in the poetry category of the 2025 A-mu-sing Contest. The poem is designed to teach about word (or term) frequencies in text mining which involves thoughtful construction in defining the actual measurements to use. Instructors might have students go over this poem and then discuss how to define what words or stems of words should be included or excluded in a different textual application. A live performance of the poem at the USCOTS 2025 banquet can be found at https://youtu.be/YpoPDmSxt4o?t=2326.
A short song describing the benefits of blocking in experimental design by Heather Nichols, a teacher at Oak Creek High School in Wisconsin. It may be sung to the tune of the traditional Scottish Gaelic tune, "Bunessan." The Randomization Song teaches the benefits of random assignment in an experiment. Randomization is relied upon to reduce bias or control effects of confounding variables and create comparable treatment groups. It also alludes to the use of random sampling and the generalization that allows so an instructor can make a comparison between random assignment and random sampling. The song was part of a pair of songs (along with the Blocking Song) that took the grand prize for the 2025 A-mu-sing Contest. A live performance of both the Blocking Song and the Randomization Song at the USCOTS 2025 banquet can be seen at https://youtu.be/YpoPDmSxt4o?t=1923.
A short song describing the benefits of blocking in experimental design by Heather Nichols, a teacher at Oak Creek High School in Wisconsin. It teaches students that blocking reduces variability in the response variable by creating groups of similar experimental units to see how they respond differently to the treatments in the experiment. The song was part of a pair of songs (along with the Randomization Song) that took the grand prize for the 2025 A-mu-sing Contest. A live performance of both the Blocking Song and the Randomization Song at the USCOTS 2025 banquet can be seen at https://youtu.be/YpoPDmSxt4o?t=1923.
A joke to initiate a conversation about the importance of understanding your Sampling Frame when conducting surveys. The joke was written by Larry Lesser from The University of Texas at El Paso in 2021.
A cartoon that can be used to discuss the importance of investigating and understanding the outliers in data sets. The cartoon was used in the January 2023 CAUSE cartoon caption contest and the winning caption was written by Amelia Williams, a student at University of Toronto. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
A cartoon that can be a vehicle to discuss the old GIGO adage (Garbage In Garbage Out) indicating how poor data may well produce poor results. The cartoon was used in the September 2022 CAUSE cartoon caption contest and the winning caption was written by Jonathan Boucher, a student at Colorado University in Boulder. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.