Out-of-class

  • A collection of Statistics related Haikus collected by Nicholas Horton from his Math 190 (statistical Methods for Undergraduate Research) course at Smith College in Spring, 2010. These are included in the Statistics Haiku Project at http://www.math.smith.edu/~nhorton/haikustat.html
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  • A joke to teach the meaning of type I error by University of Texas at El Paso professor of Mathematical Sciences, Lawrence Mark Lesser (1964-) and Ohio State Unviersity PRofessor of Statistics Dennis K. Pearl (1951-).
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  • A joke to use when teaching about choices of binary response data models like the Logistic or Probit models by University of Texas at El Paso professor of Mathematical Sciences, Lawrence Mark Lesser (1964-).
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  • A joke that can be used when teaching six sigma process control ideas or chi-squared goodness-of-fit tests.
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  • Although numbers don't lie, it's rather annoying that they don't tell us everything we need to know. Maybe it's because 99% of all statistics only tell us 49% of the story. is a quote by American investment author Ron DeLegge II (1971 - ). The quote appears in his book "Gents With No Cents" published in 2011 by Half Full Publishing Group.
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  • This is an extensive collection (and a continuously expanding collection) of applets on topics that include probability, descriptive statistics, sampling distributions, Monte Carlo simulation, Buffon's coin problem, chi-square, p-values, correlation, and more. There is even a random number generator that is part of the collection.
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  • This simulation allows you to roll two dice and compare empirical and probability histograms for the sum or product of the two outcomes.
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  • This hour long radio podcast focuses on stochasticity, or randomness. According the website: "Stochasticity (a wonderfully slippery and smarty-pants word for randomness), may be at the very foundation of our lives. To understand how big a role it plays, we look at chance and patterns in sports, lottery tickets, and even the cells in our own body. Along the way, we talk to a woman suddenly consumed by a frenzied gambling addiction, meet two friends whose meeting seems to defy pure chance, and take a close look at some very noisy bacteria." Several guests appear in this radio podcast, including Deborah Nolan.
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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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  • September 14, 2010 T&L webinar presented by Thomas Moore(Grinnell College) and hosted by Jackie Miller(The Ohio State University). Permutation tests and randomization tests were introduced almost a century ago, well before inexpensive, high-speed computing made them feasible to use. Fisher and Pitman showed the two-sample t-test could approximate the permutation test in a two independent groups experiment. Today many statistics educators are returning to the permutation test as a more intuitive way to teach hypothesis testing. In this presentation, I will show an interesting teaching example about primate behavior that illustrates how simple permutation tests are to use, even with a messier data set that admits of no obvious and easy-to-compute approximation.
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