Resource Library

A poem with an accompanying video reading of the poem by Micael A. Posner from Villanova University that 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 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 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 haiku poem written in 2019 by Larry Lesser from The University of Texas at El Paso to spark discussion about multivariable thinking and confounding variables, which are a major emphasis of the 2016 GAISE College Report.  The poem is part of a collection of 8 poems published with commentary in the January 2020 issue of Journal of Humanistic Mathematics.

A cartoon that invites conversation about the type of biases that may result from the way a pollster handles the logistics of taking a survey and thus the importance of careful planning.  The cartoon was used in the February 2022 CAUSE cartoon caption contest and the winning caption was written by Don Bell-Souder a student at University of Colorado, Boulder. Two alternative captions with the same basic learning object are “Selection bias is in the eye of the beholder” written by Sarah Arpin and “ACME polling finds that bootstrapping still reflects self-reporting bias.” Written by Rosie Garris who are also both students at University of Colorado, 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 song for discussion of the uses of weighting. In particular, Verse 1 hits the weighted mean (with a nod to Simpson’s paradox), Verse 2 connects with how/why poll data are weighted to help the sample more accurately reflect population characteristics, which can launch a discussion of what we adjust for (probability, sample design, demographics) and how (raking, matching, propensity weighting). This can be supported by examples in GAISE (https://www.amstat.org/docs/default-source/amstat-documents/gaisecollege...) and apps (e.g., https://sites.psu.edu/shinyapps/2018/12/03/weight-adjustment-in-surveys/). Finally, the Bridge touches on weighted regression. Lyrics by Larry Lesser from The University of Texas at El Paso; may be sung to the tune of the 1981 hit "The Waiting" by Tom Petty.  The song received an honorable mention in the 2023 A-mu-sing competition.  Thanks to UTEP’s Jose Villalobos for the song title and for contributing backing vocals and guitar to Larry’s on the recording.

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.

A cartoon that highlights the importance of details in designing an experiment that have important repercussions for one’s ability to interpret the results. The cartoon was used in the May 2022 CAUSE cartoon caption contest and the winning caption was written by Jim Alloway from the 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.