Resource Library

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 live performance of both the Blocking Song and the Randomization Song at the USCOTS 2025 banquet can be seen at https://youtu.be/YpoPDmSxt4o?t=1923.

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 live performance of both the Blocking Song and the Randomization Song at the USCOTS 2025 banquet can be seen at https://youtu.be/YpoPDmSxt4o?t=1923.

This poem, with an accompanying video reading of the poem by Michael A. Posner from Villanova University, 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 live performance of the poem at the USCOTS 2025 banquet can be found at https://youtu.be/YpoPDmSxt4o?t=2326.

This cartoon caption can be used to discuss how the interpretation of data must be informed by a knowledge of the how the data was generated. The cartoon was used in the May 2025 CAUSE cartoon caption contest and the winning caption was written by Sara Colando, a student at Carnegie Mellon 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 can be used to discuss concepts about the probability of the intersection of two events.  The cartoon was used in the April 2025 CAUSE cartoon caption contest and the winning caption was written by Cigdem Sirin 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 can be used to illustrate the idea that over-cleaning or over-smoothing messy data may risk the loss of important information and yield a misleading characterization of the data. The cartoon was used in the March 2025 CAUSE cartoon caption contest and the winning caption was written by Jerry Nedelman from the TB Alliance.  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 can be used to illustrate the difference between continuous and discrete distributions. The cartoon was used in the February 2025 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. 

This cartoon caption can be used in discussing how simple random sampling can be improved upon by taking obvious explanatory factors into account. The cartoon was used in the October 2024 CAUSE cartoon caption contest and the winning caption was written by high school student Jackson Lin, from North Carolina School of Science and Mathematics.  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 can be used in discussing the impact of outliers/influential points on inferential procedures.  The cartoon was used in the August 2024 CAUSE cartoon caption contest and the winning caption was written by Kylee Regennitter, a student at University of Nebraska in Lincoln.  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 illustrates the idea that an inappropriate process of collecting data may be a confounder in its interpretation. The cartoon was used in the March 2024 CAUSE cartoon caption contest and the winning caption was written by Grant Zou a student at the University of Virginia.  The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.