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Estimation Principles

  • A sketch by Anastasia Mandel reinterpreting "Mont Sainte-Victoire" by Paul Cezanne (1898) with the statistical caption "A skewed distribution, but the same mountain (always look at things from different angles)." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions written by Stan Lipovetsky and Igor Mandel that took first place in the cartoon & art category of the 2009 A-Mu-sing contest sponsored by CAUSE. The collection and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • A sketch by Anastasia Mandel reinterpreting "Full Cry" by Heywood Hardy (1892) with the statistical caption "Random noise." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions written by Stan Lipovetsky and Igor Mandel that took first place in the cartoon & art category of the 2009 A-Mu-sing contest sponsored by CAUSE. The collection and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • A cartoon to teach the idea that sampling variability depends on the size of the sample, and not on the size of the population (as long as the sample is a small part of the population). Cartoon drawn by British cartoonist John Landers based on an idea from Dennis Pearl. Free to use in the classroom and for course websites.

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  • A cartoon to teach about the need to think carefully about the assumptions underlying a statistical model (also uses the idea that you can multiply chances for independent events to find the chance that they all occur). Drawn by British cartoonist John Landers based on an idea from Dennis earl. Free to use in the classroom and on course websites.

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  • A cartoon to teach about the interpretation of confidence statements. The cartoon plays on the idea of what would happen if the same process was repeated over-and-over again. 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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  • Song about bootstrap resampling methods and their history. May be sung to the tune of Don McLean's 1971 song "American Pie." Lyrics by Giles Hooker (May, 2004). This song is part of the "Stanford Statistics Songbook" found at www.bscb.cornell.edu/~hooker/StanfordStatisticsSongbook.pdf Free to use for non-commercial educational purposes. Contact author to use in publications or for commercial purposes. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • Hiawatha Designs an Experiment is a poem by English statistician Sir Maurice George Kendall (1907 - 1983). The poem can be used in teaching about the trade-off between reliability and bias found in many inference problems and in designing experiments and interpreting the results of an ANOVA. The poem was originally published in "The American Statistician" December, 1959.

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  • The primary themes of this parody involve elementary probability and the importance of graphical summaries. It may be sung to the tune of "Big Yellow Taxi" by Canadian songwriter Joni Mitchell, 1970. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • A cartoon to teach about confidence intervals. 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 group activity illustrates the concepts of size and power of a test through simulation. Students simulate binomial data by repeatedly rolling a ten-sided die, and they use their simulated data to estimate the size of a binomial test. They carry out further simulations to estimate the power of the test. After pooling their data with that of other groups, they construct a power curve. A theoretical power curve is also constructed, and the students discuss why there are differences between the expected and estimated curves. Key words: Power, size, hypothesis testing, binomial distribution
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