Resource Library

Statistic Acrostic is a poem by statistics educator Lawrence Mark Lesser and biostatistician Dennis K. Pearl that covers several statistical concepts using only 26 words (one starting with each letter of the alphabet). It was written in 2008 as a response to an example and challenge from JoAnne Growney in her poem “ABC, an Analytic Geometry Poem” in a 2006 article in Journal of Online Mathematics and Its Applications.  To expand the usefulness of this form for educational objectives, a teacher could have students not follow the 26-letter alphabet, but generate an acrostic from a statistics word or phrase.

A song to teach about when the mean versus the median is better for describing a distribution. The lyric was authored by Lawrence Mark Lesser from The University of Texas at El Paso. The song may be sung to the tune of Taylor Swift's Grammy-winning 2010 hit "Mean". Free for use in non-commercial teaching.

A song presenting common hypothesis tests and the steps in doing them with lyrics by Jamie Tan Xin Yee, Joelyn Chong, Deston Tang, Christine Sia, Nellie Lee, Josiah Tan, and Lee Yi Yuan who were all students at Singapore Management University taught by Rosie Ching Ju Mae.  May be sung to the tune of "LOVE" by Bert Kaempfert and Milt Gabler and recorded by Nat King Cole in 1965.  The vocals and guitar soundtrack on the audio were done by Joelyn. Editing of the soundtrack was done by the entire student team.The song placed tied for second in the 2023 A-mu-sing competition (see associated publicity).

A cartoon suitable for use in teaching about model fitting techniques and the different messages a visualization puts forward based on the model used to fit the data . The cartoon is number 2048 (Sept, 2018) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom and on course web sites under a creative commons attribution-non-commercial 2.5 license.

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.