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Elementary Probability

  • Song addresses the famous probability example of Birthday Problem by contrasting the often confused events of "some people matching" with "someone matches with ME". May be sung to the tune of "Happy Birthday to You" (Mildred J. Hill and Patty Smith Hill). Originally appeared in Winter 2002 "STATS". Recorded June 26, 2009 at the OSU Whisper Room: Larry Lesser, vocals/guitar; Justin Slauson, engineer.
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  • This poem, by North Carolina State University Emeritus Professor of Physics Jasper D. Memory (1935 - ) is designed to teach the difference between the probability of having a disease given a positive screening test and the probability of a positive test result given you have the disease. The poem was published in the October, 2007 issue of "Mathematics Magazine" volume 80 p. 273,
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  • Statistician's "breakup" song is filled with 2 dozen puns from a variety of (mostly first-year) statistical terms. Song is a 12-bar blues, with the words in parentheses more spoken than sung during the final 2 bars of each 12. Appeared in Winter 2002 "STATS" and Spring 2004 "The Pi".
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  • Song describes conditions for using the t distribution and mentions its inventor William Gosset (and his pseudonym, Student). May be sung to the tune of "Let it Be" (McCartney/Beatles). Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.
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  • This article, in a series, describes a game, which tests opposing strategies through aspects of experiemental design.
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  • This website provides the URL of a Java applet and steps for using it. Here, students can manipulate the size of the circle and the rectangle to explore the probability that a point in the rectangle is also in the circle.
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  • This activity addresses the concept of sample space. It provides a multi-step procedure and three handouts, which accompany the activity. It addresses events and the availability misconception as well as grouping and forming committees.
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  • This site provides an outline of an activity for introducing Bayes' Theorem and conditional probability.
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  • The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. This site is primarily concerned with the stand-alone WinBUGS 1.4.1 package, which has a graphical user interface and on-line monitoring and convergence diagnostics. This program can be downloaded for free from the site.

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  • This section of an online textbook discusses calculating the exact probability using observed sets of frequencies, constructing frequency tables, and computing p-values. Exercises and answers are provided.
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