Variable Classification

  • This issue contains articles about binomial confidence intervals; the team effect in stock car racing; using multiple tests (one-sample t-test and sign test); the "two-envelope exchange paradox" (similar to the Monty Hall problem) with discussions of expectation, likelihood, and inference; regression line vs. trend line; calculations of standard normal table values and pi; teaching at a small liberal arts college; modeling extreme events.
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  • This issue contains articles about steroids in baseball; finding ways to make learning statistics fun; an interview with Joan Garfield about Statistics Education; an introduction to response surface methodology; and a look at the vocabulary used in experimental design.
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  • This issue contains articles about Karl Pearson (150 years after his birth); finding more ways to make learning statistics fun; simulating capture-recapture sampling in Excel and by hand; common misconceptions in statistics; a correlation-based puzzler and a STAT.DOKU puzzle.

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  • In this module, students can test their knowledge of levels of measurement by attempting to determine the the level of measurement of ten different variables. For each variable, a statement is also provided and students can indicate whether the statement about the variable is valid or invalid (given the way in which the variable was measured). There is also a brief "refresher" included here about levels of measurement.

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  • January 26, 2010 webinar presented by Alicia Gram, Smith College, and hosted by Leigh Slauson, Capital University. This webinar describes an activity that uses data collected from an experiment looking at the relationship between two categorical variables: whether a cotton plant was exposed to spider mites; and did the plant contract Wilt disease? The activity uses randomization to explore whether there is a difference between the occurrence of the disease with and without the mites. The webinar includes a discussion of the learning goals of the activity, followed by an implementation of the activity then suggestions for assessment. The implementation first uses a physical simulation, then a simulation using technology. (Extra materials, including Fathom instructions for the simulation, available for download free of charge).

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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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  • This joke can be used to motivate class discussions on the assumptions underlying drawing conclusions from data (especially the assumption of stationarity). The joke is a revision of a story in "The Angel's Dictionary: A modern tribute to Ambrose Bierce" by Edmund Volkart - also quoted in "Statistically Speaking: A dictionary of Quotations" by Carl Gaither and Alma Cavazos-Gaither (page 62). The revision (to make the story suitable for classroom use) was written by Dennis Pearl, The Ohio State University.

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  • This collection of datasets comes from several phases of drug research. Each dataset comes with a full description and questions to answer from the data.
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  • This Department of Energy website provides weekly average gasoline prices for several regions, states and cities. The averages are produced from a weekly survey of around 800 retail gasoline stations. The site includes information on data collection methods, survey methodology and historical data.
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  • This article describes a dataset on the readability of booklets about cancer and the reading levels of patients with cancer. Students should be familiar with scales of measurement, data reduction, measuring center, constructing and interpreting displays, and reaching conclusions in real problems. Key Words: Ordinal data, Means, Medians, Histograms
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