Resource Library

A cartoon suitable for use in teaching about the idea of a falsifiable hypothesis. The cartoon is number 2078 (November, 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 suitable for use in teaching about publication bias and the small sample caution in hypothesis testing. The cartoon is number 2020 (July, 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.

Summary: This High School AP activity examines whether students can tell the difference between Coke^TM and Pepsi^TM by taste? During the “tasting part”, data are collected and the class keeps track of how many students can differentiate between Coke and Pepsi. During the “simulation part” of the activity, a simulation is conducted with dice. Finally, students compare their classroom results in the taste test with the simulated results about what would happen when subjects just guess randomly from the three possible choices. The activity is described in F. Bullard, “AP Statistics: Coke Versus Pepsi: An Introductory Activity for Test of Significance: AP Central – The College Board,” 2017 on the AP Central website at https://apcentral.collegeboard.org/courses/ap-statistics/classroom-resources/coke-versus-pepsi-introductory-test-significance

Specifics: The activity is performed in the following steps:

1. The Tasting part:
   1. First, two students will label three cup positions “A,” “B,” and “C.” Then they will roll a die and pour drinks into the cups such that all combinations of two of one drink and one of the other are represented, and the die roll makes each combination equally likely and keep track of the treatment.
   2. Students will be called out into the hall one by one to taste the three drinks and decide which cup contains the different drink. They do not need to identify the drinks as Coke or Pepsi, they only have to identify the cup containing the different soda, either A, B, or C.
2. The Simulation part:
   1. The next stage of the discussion is to ask the students how many correct identifications they need before they can conclude that people were not just randomly guessing: “11 out of 30 is more than a third, but not enough more to be convincing, right?” Students will probably volunteer different dividing lines, but they will not be good at defending them. At the point when all the students understand the question but are unsure of how to answer it, the dice should be introduced into the activity.
   2. The students can suggest a simulation in which two die outcomes (say, 1 and 2) are considered a correct cup identification, and the other four die outcomes (say, 3, 4, 5, and 6) are considered incorrect cup identifications. Demonstrate by rolling a set of dice or one die many times. You should have as many die rolls as there are subjects in the study. Count the 1s and 2s. Suppose there are 8 out of 30 that “guessed correctly.” On your number line at the blackboard, make an X over the number 8. The students or group of students should do five or 10 simulations each (it’s good to have about 100—200 simulations) and then come to the blackboard and stack their Xs over the appropriate integers, making a histogram of the distribution of “number of correct cup identifications if everyone is randomly guessing.”
3. Conclusion:
   1. Upon the conclusion of the tasting, the number of correct identifications is then counted. At this point, if the number is unusually high (say, 18 out of 30), then most students are prepared to conclude (correctly) that there is evidence that at least some people can tell the difference between Coke and Pepsi.
   2. Some statement like this would be great: “If everyone were randomly guessing, we would almost never see 18 students get it right by luck, because we did that 100 times with dice, and the highest we ever got was 16, and that was only once.”
   3. In the author’s experience, usually, about half or a little more will identify the correct drink. When the author, did this activity with a class: 13 out of 21 students correctly identified the different drinks.

(Resource photo illustration by Barbara Cohen, 2020; this summary compiled by Bibek Aryal)

A poem written in 2019 by Larry Lesser from The University of Texas at El Paso to discuss statistics examples involving social justice, inspired by his paper in March 2007 Journal of Statistics Education. The poem is part of a collection of 8 poems published with commentary in the January 2020 issue of Journal of Humanistic Mathematics.

The researcher armed with a confidence interval, but deprived of the false respectability of statistical significance, must work harder to convince himself and others of the importance of his findings. This can only be good. is a quote by British statistician Michael W. Oakes. The quote is found in his 1986 book "Statistical Inference: a Commentary for the Social and Behavioural Sciences" published by John Wiley & Sons.

A joke for discussing the over-use of hypothesis testing methods.  The joke was written in April 2019 by Larry Lesser from The University of Texas at El Paso.

A fun song about the average by American humorist and singer-songwriter Carla Ulbrich. The song was a finalist in the novelty category of the 2018 USA Songwriting Competition.  The song is also available at www.theacousticguitarproject.com/artist/carla-ulbrich/ and more about the singer can be found at her website at www.carlau.com. For classroom use, you might ask which lines in "Totally Average Woman" refer to ways in which the woman in the song is at the mean, and which refer to ways in which she is at the median. Permission from singer is for free use for teaching in classroom and course websites with attribution. Commercial users must contact the copyright holder.

A song to be used in discussing the idea that the null hypothesis represents the model of no effect (with several common examples). The original music and lyrics were written in 2017 by Greg Crowther from Everett Community College. The song won an honorable mention in the 2017 A-mu-sing contest. In the current 2018 version the music is by Greg Crowther and the revised lyrics and vocals are by Greg Crowther and Larry Lesser from University of Texas at El Paso.

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.

Dr. Kuan-Man Xu from the NASA Langley Reserach Center writes, "A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. "