Categorical Methods

  • A statistics scramble that might be used in teaching goodness-of-fit significance tests. A set of five anagrams must be solved to reveal the letters that provide the answer to the clue in the cartoon. The cartoon was drawn by British cartoonist John Landers based on an idea by Dennis Pearl. Free for use on course websites, or as an in-class, or out-of class exercise.

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  • This is my take on the ubiquitous M&Ms counting activity. Each student records the color proportions in a fun-size bag of M&Ms. We pool the class data and run a Chi-Square goodness-of-fit test to determine whether or not the color proportions match those claimed on the manufacturer's website. We consistently find that the proportions do not match. The blue M&Ms, in particular, are underrepresented. This activity also includes a review of the 1-proportion z confidence interval.

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  • Song about the pleasure of teaching statistics when the class is engaged. May be sung to the tune of John Lennon and Paul McCartney's 1963 song "I Want to Hold Your Hand." Lyrics by Armin Schwartzman (December, 2003). This song is part of the "Stanford Statistics Songbook" found at www.bscb.cornell.edu/~hooker/StanfordStatisticsSongbook.pdf Free to use for non-commercial educational purposes. Contact author to use in publications or for commercial purposes. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • Song about the need to show a significant result in order to have a manuscript published. May be sung to the tune of Robert Feldman, Gerald Goldstein and Richard Gottehrer's 1963 song "My Boyfriend's Back," popularized by The Angels. Lyrics by Marc Coram and Matthew Finkelman (December, 2003). This song is part of the "Stanford Statistics Songbook" found at www.bscb.cornell.edu/~hooker/StanfordStatisticsSongbook.pdf Free to use for non-commercial educational purposes. Contact author to use in publications or for commercial purposes. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • Empty Cells in Contingency Tables is a poem that can be used to teach the difference between random zeros and structural zeros in contingency tables. The poem was written by Maarten Manhoff (1972- ), the pen name for Ernst Wit of Lancaster University in the United Kingdom

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  • A cartoon to teach about the concept of independent versus dependent variables. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

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  • In this activity, students explore calculations with simple rates and proportions, and basic time series data, in the context of news coverage of an important statistical study. From 1973 to 1995, a total of 4578 US death penalty cases went through the full course of appeals, with the result that 68% of the sentences were overturned! Reports of the study in various newspapers and magazines fueled public debate about capital punishment.
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  • Tutorial on the ANOVA test in statistics and probability, with a description, formulas, example, and a calculator applet. This is part of the larger site Virtual Statistician at http://web.mst.edu/~psyworld/virtualstat.htm
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  • Using cooperative learning methods, this lesson introduces distributions for univariate data, emphasizing how distributions help us visualize central tendencies and variability. Students collect real data on head circumference and hand span, then describe the distributions in terms of shape, center, and spread. The lesson moves from informal to more technically appropriate descriptions of distributions.
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  • Using cooperative learning methods, this activity helps students develop a better intuitive understanding of what is meant by variability in statistics. Emphasis is placed on the standard deviation as a measure of variability. This lesson also helps students to discover that the standard deviation is a measure of the density of values about the mean of a distribution. As such, students become more aware of how clusters, gaps, and extreme values affect the standard deviation.
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