This cartoon caption is intended to emphasize the identification of seasonal effects in time series plots. The cartoon was used in the November 2023 CAUSE cartoon caption contest and the winning caption was written by Regina Lisinker, a student at the University of Minnesota. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
This cartoon caption is intended to emphasize the theme that whether we're looking at climate data or any other field, recognizing and managing variation is key to drawing meaningful insights from data and making reliable forecasts. The cartoon was used in the October 2023 CAUSE cartoon caption contest and the winning caption was written by Ian Bang, a student at the Friends Seminary in New York City. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
This cartoon caption might be used in announcing hackathon style events and in discussing the importance of collaboration in a team-based search for meaning in data. The cartoon was used in the September 2023 CAUSE cartoon caption contest and the winning caption was written by Larry Lesser from The University of Texas at El Paso. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
This cartoon caption is a funny way to start a conversation about the difference between a regression fit and a line plot and the type of data involved. The cartoon was used in the August 2023 CAUSE cartoon caption contest and the winning caption was written by Javier Lopez, a student at Penn 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.
This cartoon caption is a good reminder that graphical presentations are more readily digested by viewers than mere statistical summaries. The cartoon was used in the July 2023 CAUSE cartoon caption contest and the winning caption was written by Carolyn Showalter from Ocean County College. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
This cartoon caption is a good reminder that the 0’s and 1’s underlying the computational aspects of Data Science helps to transform data into useful knowledge. The cartoon was used in the June 2023 CAUSE cartoon caption contest and the winning caption was written by Julie Skokie from North Broward Preparatory School. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
This cartoon caption is a good reminder that graphics can convey a more convincing and realistic view of what data are telling us than merely presenting numerical or tabular results. The cartoon was used in the May 2023 CAUSE cartoon caption contest and the winning caption was written by Jim Alloway from EMSQ Associates. 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 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.
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.
The lyrics for “The Statistician’s Song” were written by Paul Velleman from Cornell University as a parody of Tom Lehrer’s 1974 “The Professor’s Song” published in American Mathematical Monthly and sung to the tune of “If You Give Me Your Attention,” from the play Princess Ida by Gilbert and Sullivan. The song won third place in the Song/Video category of the 2021 A-mu-sing Contest. The song facilitates discussion of the characteristics of good teaching in statistics (e.g. stressing real world applications and gaining insights from evidence over focusing on esoteric theory and memorization of formulas).