This poem by Kelly Godwin from Cal Poly, San Luis Obispo, is a parody of Robert Frost's popular 1915 poem "The Road Not Taken" and took first place in the poetry category of the 2021 A-mu-sing Contest. The poem is designed to facilitate discussions of the advantages of Bayesian inference methodology.
A joke written by Evan Wimpey from Elder Research, Inc. that took first place in the Joke/Cartoon category of the 2021 A-mu-sing Contest. The joke may be used in discussing fundamentals of Bayesian inference and to challenge students to describe what it might mean to have a "weak prior" in the situation in the joke.
The CI Hammer video is part of a series of musical summary reviews of different statistical and data science topics by Professor Rafael de Andrade Moral from Maynooth University in Ireland, including a set of three that won the grand prize in the 2021 A-mu-sing Contest.
The lyrics reviewing Confidence Intervals and associated learning objectives were written and the video was produced and performed by Dr. Moral, while the music may be sung to the tune of Ghost's 2016 hit “Square Hammer.”
The lyrics and music for this rap were written by Parker Kain, an undergraduate student at Northern Kentucky University, that took second place in the Song/Video category of the 2019 A-mu-sing contest (Parker Kain also performed the song at the banquet of the 2019 USCOTS). The song facilitates discussion of the different components of a confidence interval (estimate, margin of error, and confidence multiplier) and interpreting the interval properly and in the context of the real world problem under study.
A cartoon that can be used in discussing how choosing an appropriate sample size must balance budget and logistics along with statistical power. The cartoon was used in the April 2023 CAUSE cartoon caption contest and the winning caption was written by retired AP Statistics teacher Jodene Kissler. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University. An alternate caption for the cartoon might be “The Negative Correlation Moving Company had trouble holding on to their shorter employees,” that can be used to discuss the difference between positive and negative associations.
A cartoon that can be a vehicle to discuss the value of approximations in statistical inference and the need to check the fit of models. The cartoon was used in the October 2022 CAUSE cartoon caption contest and the winning caption was written by Eric Vance, from University of Colorado 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.
A cartoon providing a nice way to introduce the value of data mining for finding patterns in data but not as a gold standard for inference. The cartoon was used in the July 2020 CAUSE cartoon caption contest and the winning caption was written by Charles Eugene Smith from North Carolina State University. 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 provides a clever way to introduce neural networks and machine learning topics. The cartoon was used in the June 2020 CAUSE cartoon caption contest and the winning caption was written by Luis Rivera-Galicia from Alcala University in Spain. 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 to help discuss both the value and limits of making predictions with large amounts of data. The cartoon was drawn by American cartoonist Jon Carter in 2015.
A song designed to assist in teaching the basics of Multi-Armed Bandits, which is a type of machine learning algorithm and is the foundation for many recommender systems. These algorithms spend some part of the time exploiting choices (arms) that they know are good while exploring new choices. The song (music and lyrics) was written in 2021 by Cynthia Rudin from Duke University and was part of a set of three data science oriented songs that won the grand prize in the 2023 A-mu-sing competition. The lyrics are full of double entendres so that the whole song has another meaning where the bandit could be someone who just takes advantage of other people! The composer mentions these examples of lines with important meanings:
"explore/exploit" - the fundamental topic in MAB!
"No regrets" - the job of the bandit is to minimize the regret throughout the game for choosing a suboptimal arm
"I keep score" - I keep track of the regrets for all the turns in the game
"without thinking too hard," - MAB algorithms typically don't require much computation
"no context, there to use," - This particular bandit isn't a contextual bandit, it doesn't have feature vectors
"uncertainty drove this ride." - rewards are probabilistic
"I always win my game" - asymptotically the bandit always finds the best arm
"help you, decide without the AB testing you might do" - Bandits are an alternative to massive AB testing of all pairs of arms
"Never, keeping anyone, always looking around and around" - There's always some probability of exploration throughout the play of the bandit algorithm