Faculty

  • A song parody to be sung about one's favorite statistics course. The lyrics won an honorable mention in the song category of the 2011 CAUSE A-Mu-sing contest and were written by Robert Carver of Stonehill College. The song may be sung to the tune of George and Ira Gershwin's 1937 classic "They Can't Take That Away from Me." Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • A poem useful in teaching aspects about hypothesis testing, especially the caveat that unimportant differences may be deemed significant with a large sample size. The poem was written by Mariam Hermiz, a student at University of Toronto, Mississauga in Fall 2010 as part of an assignment in a biometrics class taught by Helene Wagner. The poem was awarded first place in the poetry category of the 2011 CAUSE A-Mu-sing contest.

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  • A Haiku about the meaning of significance by Dr. Nyaradzo Mvududu of the Seattle Pacific University School of Education. The poem was awarded a tie for second place in the 2011 CAUSE A-Mu-sing competition.

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  • A song about the important contributions of Karl Pearson, Charles Spearmen, William S. Gosset, and Ronald Fisher. Lyrics written by Nyaradzo Mvududu from Seattle Pacific University. May sing to the tune of John Lennon's 1971 song "Imagine." The lyrics were awarded third place in the song category of the 2011 CAUSE A-Mu-sing competition. Musical accompaniment realization are by Joshua Lintz and vocals are by Mariana Sandoval from University of Texas at El Paso.

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  • A poem by Notre Dame College Mathematics professor Anthony Masci. The poem was awarded an honorable mention in the 2011 CAUSE A-Mu-sing competition.

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  • A song about examining the assumptions in statistical procedures especially dealing with skewed distributions. The lyrics were written by Robert Carver of Stonehill College and were awarded second place in the song category of the 2011 CAUSE A-Mu-sing competition. The song is a parody of the 1961 classic pop song "Runaround Sue" written by Ernie Maresca and Dion DiMucci and sung by Dion backed by the vocal group, The Del-Satins. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • Three Haiku related to regression including the topics of checking assumptions, dealing with non-linear patterns, and partitioning sums of squares. The Haiku were written by Elizabeth Stasny of The Ohio State University and were awarded a tie for second place in the poetry category of the 2011 CAUSE A-Mu-sing competition.

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  • A song for teaching ideas about hypothesis testing including interpretation of significance and the difference between significance and practical relevance. Lyrics written by Denise Tran, a student at University of Toronto, Mississauga in Fall 2010 as part of an assignment in a biometrics class taught by Helene Wagner. May be sung to the tune of the 2001 Grammy award winning song "Drops of Jupiter (Tell Me)" by the rock band Train (Patrick Monahan, Robert Hotchkiss, James Stafford, Scott Underwood, and Charlie Colin). The song won first place in the song category and best overall entry in the 2011 CAUSE A-Mu-sing competition.

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  • TeachingWithData.org is portal of teaching and learning resources for infusing quantitative literacy into the social science curriculum. A Pathway of the National Science Digital Library, TwD aims to support the social science instructor at secondary and post-secondary schools by presenting user-friendly, data-driven student exercises, pedagogical literature, and much more! Resources are available on a wide range of topics and disciplines.

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  • August 10, 2010 T&L webinar presented by Diane Fisher (University of Louisiana at Lafayette), Jennifer Kaplan (Michigan State University), and Neal Rogness (Grand Valley State University) and hosted by Jackie Miller(The Ohio State University). Our research shows that half of the students entering a statistics course use the word random colloquially to mean, "haphazard" or "out of the ordinary." Another large subset of students define random as, "selecting without prior knowledge or criteria." At the end of the semester, only 8% of students we studied gave a correct statistical definition for the word random and most students still define random as, "selecting without order or reason." In this session we will present a classroom approach to help students better understand what statisticians mean by random or randomness as well as preliminary results of the affect of this approach.
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