Data Collection

  • This hands-on activity is appropriate for a lab or discussion section for an introductory statistics class, with 8 to 40 students. Each student performs a binomial experiment and computes a confidence interval for the true binomial probability. Teams of four students combine their results into one confidence interval, then the entire class combines results into one confidence interval. Results are displayed graphically on an overhead transparency, much like confidence intervals would be displayed in a meta-analysis. Results are discussed and generalized to larger issues about estimating binomial proportions/probabilities.
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  • In this hands-on activity, students count the number of chips in cookies in order to carry out an independent samples t-test to see if Chips AhoyŒ¬ cookies have a higher, lower, or different mean number of chips per cookie than a supermarket brand. First there is a class discussion that can include concepts about random samples, independence of samples, recently covered tests, comparing two parameters with null and alternative hypotheses, what it means to be a chip in a cookie, how to break up the cookies to count chips, and of course a class consensus on the hypotheses to be tested. Second the students count the number of chips in a one cookie from each brand, and report their observations to the instructor. Third, the instructor develops the independent sample t-test statistic. Fourth, the students carry out (individually or as a class) the hypothesis test, checking the assumptions on sample-size/population-shape.
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  • November 24, 2009 Activity webinar presented by Carl Lee, Central Michigan University, and hosted by Leigh Slauson, Capital University. This webinar introduces a real-time online hands-on activity database for teaching introductory statistics. One particular activity, "How well can hand size predict height?", is used to engage students with a real-time activity in order to learn bivariate relationships. Various other activities can be found at stat.cst.cmich.edu/statact. The real-time database approach speeds up the process of data gathering and shifts the focus in order to engage students in the process of data production and statistical investigation.
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  • This site funded by the Kaiser Family Foundation provides information on health care and demographics for the 50 U.S. states. Users can use interactive maps or search by particular characteristics for each state. Tables can be created and copied and there is also direct data download (in Excel format) from this site. The site includes data on median income, gender, ethnicity, medical and drug spending, HIV/AIDS rates, and over 500 other variables at the state level
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  • Do not put your faith in what statistics say until you have carefully considered what they do not say. A quote by English professor William Whyte Watt (1912 - 1996) in his book "An American Rhetoric" (Rinehart and Co.; 1958 3rd edition, page 382).

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  • If you can't measure it, I'm not interested. A quote by Canadian educator and management theorist Laurence Johnston Peter (1919 - 1990) from "Peter's People" in "Human Behavior" (August, 1976; page 9). The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • Meditation on Statistical Method is a poem by American poet and Brandeis University professor James Vincent Cunningham (1911 - 1985). The poem was originally published in "The Exclusions of a Rhyme: Poems and Epigrams" (1960; Swallow Press) and may also be found in "The collected poems and epigrams of J.V. Cunningham" (1971; Swallow Press).
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  • A series of 19 songs used to teach Structural Equations Modeling (SEM) by Alan Reifman of Texas Tech University. A video of an in-class performance of the musical on April 27, 2007, is also available at the website. The Musical took second place in the 2007 A-Mu-sing competition.
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  • This pdf text file gives a short introduction to the methods of Bayesian inference. It gives a simple example that deals with jumping a paper frog. The topics listed in this document include: An example, comparison of frequentist and Bayesian methods, credible vs. confidence intervals, choice of prior and its effect on the posterior distribution.
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  • A cartoon for general use with discussions of election polls. Cartoon by John Landers (www.landers.co.uk) based on an idea from Steve MacEachern (The Ohio State University). Free to use in the classroom and on course web sites.
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