Fun

  • A cartoon to be used for in discussing the Poisson model for the number of rare events in a fixed amount of time. The cartoon was used in the August 2018 CAUSE Cartoon Caption Contest. This caption received an honorable mention. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. The winning caption  in the August competition was "Always read the full informed consent document before signing up to be in a matched-pairs experiment," written by Greg Snow from Brigham Young University and may be found at https://www.causeweb.org/cause/resources/fun/cartoons/twins

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  • A cartoon to be used for in discussing human subjects issues during a unit on designing experiments. The cartoon was used in the August 2018 CAUSE Cartoon Caption Contest. This winning caption was submitted by Greg Snow from Brigham Young University. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. An honorable mention for a caption that also rose to the top of the judging in the August competition was "The Poisson model for rare events was about to be tested," which may be found at https://www.causeweb.org/cause/resources/fun/cartoons/twins-ii

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  • A joke to help in discussing the Geometric and Hypergeometric probability distributions.  A version of the joke was submitted to AmStat News by Sara Venkatraman, a student at Cornell University and appeared in the October, 2018 issue.  The joke was modified to relate the hypergeometric distribution to sampling without replacement by the CAUSEweb fun collection editors (Dennis Peaaerl and Larry Lesser).

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  • A light bulb joke that can be used in discussing how the choice of model might affect the conclusions drawn.  The joke was submitted to AmStat News by Robert Weiss from UCLA and appeared on page 48 of the October, 2018 edition.

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  • A joke to aid in discussing Confirmation Bias (bias introduced in surveys because respondents tend to interpret things in a way that confirms their preexisting beliefs).  The joke was written by Larry Lesser from The Universisty of Texas at El Paso and Dennis Pearl from The Pennsylvania State University in October, 2018.

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  • A joke to help in discussing Latin Square experimental designs. The joke was written by Larry Lesser from The University of Texas at El Paso in October, 2018.

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  • This song covers some major real-world examples in the history of random sampling. The lyric was written in 2017 by Lawrence M Lesser from The University of Texas at El Paso and can be sung to the tune of theHarry Casey and Richard Finch song “(Shake, Shake, Shake) Shake Your Booty” that was a 1976 #1 hit for KC and the Sunshine Band.  Audio of the parody was produced and sung by students in the commercial music program of The University of Teas at El Paso.

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  • A song about the Problem of Points, whose discussion in the 17th century led to the foundations of probability theory and expected value.  The lyric was written in 2017 by Lawrence M Lesser from The University of Texas at El Paso and may be sung to the tune of the Sting #1 1983 Grammy-winning hit “Every Breath You Take”.  The audio recording was produced by Nicolas Acedo with vocals by Alejandra Nunez Vargas, both students in the Commercial Music Program at The University of Texas at El Paso.

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  • A song to help students remember the empirical rule that it is rare to see an observation more than three sd's away from the mean, while about 19 out of 20 will fall within two sd's and about 2 out of 3 within one sd.  The lyrics were weritten in 2017 by Lawrence M Lesser from The University of Texas at El Paso and may be sung to the tune of "Material Girl" written by Peter Brown and Robert Rans and populartized by Madonna. Audio of the parody was produced by Nicolas Acedo Aguilar and sung by Alexandria Campos, students in the commercial music program of The University of Texas at El Paso.

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  • Explore the Hubble Deep Fields from a statistical point of view.  Watch out for the booby traps of bias, the vagueness of variability, and the shiftiness of sample size as we travel on a photo safari through the Hubble Deep Fields (HDFs).

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