A cartoon to use in explaining how hypothesis testing typically includes a null hypothesis that nothing is going on except random chance and p-values are calculated under that assumption. The cartoon was created by Joy Reeves from the Rachel Carson Council of Duke University and took first place in the cartoon/joke category of the 2025 A-mu-sing competition.
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 that can be used to discuss the multiple testing issue and the concept of p-hacking. The cartoon was used in the June 2021 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 cartoon that can be used to discuss the importance of using a paired analysis to reduce the variability in the response for a heterogeneous population. The cartoon was used in the February 2021 CAUSE cartoon caption contest and the winning caption was written by Jeremy Case from Taylor 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 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 for discussing how subgroup analyses often lead to false positive results (using the comical idea of someone studying your study by having both treatment arms give a placebo). The cartoon is #2726 in the web comic XKCD created by Randall Munroe.
A cartoon for describing both issues associate with meta analyses and with the large number of unreplicated scientific studies. The cartoon is #2755 in the web comic at XKCD.com by Randall Monroe (see https://xkcd.com/2755/).
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.