Statistical Inference & Techniques

  • This cartoon was created by Martha Pienkowski, an undergraduate student at the University of Toronto at Mississauga, and won an honorable mention in the 2019 A-mu-sing Contest.  The cartoon reviews a comparison about the assumptions and use among various hypothesis test methods.  The cartoon compares the z-test, the t-test, and nonparametric alternatives like the sign test and the Wilcoxon test in paired and unpaired situations.

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  • This cartoon was created by Austin Boyd from University of Tennessee and took first place in the cartoon category of the 2019 A-mu-sing Contest.  The cartoon provides a humorous way to facilitate conversation about the multiple comparisons caveat (that the chance of getting at least one significant result grows with the number of things being tested) and the large sample caveat (that it is more likely to see small p-values with smaller effect sizes when you have a larger sample size).

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  • This poem was written by undergraduate students Gill Marjorie Onate and Muzaffar Bhatti from University of Toronto Mississauga, and was given an honorable mention in the poetry category of the 2019 A-mu-sing competition.  The poem is designed to aid discussions about when a nonparametric test might be used instead of a normal theory test and the difference between paired and unpaired data.

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  • A poem reflecting on Type I errors and the use of the null hypothesis in testing by Micah Wascher, a high school student at North Carolina School of Science and Mathematics.  The poem won an honorable mention in the 2025 A-mu-sing Contest. 

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  • Lyrics by John Bailer from Miami University about the value of successful statistical modeling that won an honorable mention in the 2025 A-mu-sing Contest. The song is a parody of the 1972 hit song by Johnny Nash "I Can see Clearly Now" and the vocals on the audio were performed by Kent Peterson from Oxford Presbyterian Church in Miami Ohio.  In using the song for teaching, John suggests that each verse could be connected to a question or two.  Here are examples:

    Verse 1:  How does an effective visualization reveal pattern? What types of patterns might emerge? How might such patterns be captured in a model?

    Verse 2: What are ways variables are 'engineered' as part of an analysis?

    Verse 3: How does the introduction of a confounder in a model potentially impact the estimated coefficients of other variables in a model?

    Verse 4: AUC* is one way the predictive quality of a model is described. What are other features of a useful model?

    * AUC stands for Area Under the Curve for the Receiver Operator Characteristic

    Bridge:  Residuals following a normal distribution are expected for some types of models. What other distributions might be expected? What else might be learned from the residuals?

    Verse 5: Why are we more confident with interpolations than extrapolations?

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  • "P-value's More than Alpha" is a music video by David Yew, an undergraduate student at Singapore Management University, that reviews introductory normal theory testing.  The music is a fun parody of Billy Joel's 1989 hit song "We Didn't Start the Fire" and took second place in the 2025 A-mu-sing Contest. David also credits his statistics instructor, Rosie Ching, for providing feedback.

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  • A satirical song about data science written by Dick De Veaux from Williams College that received an honorable mention in the 2025 A-mu-sing Contest. The song lampoons arguments over control of the field of data science and its defining characteristics.

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  • 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.

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  • 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.

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  • 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.

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