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Sampling & Survey Issues

  • A haiku poem written in 2019 by Larry Lesser from The University of Texas at El Paso to spark discussion about multivariable thinking and confounding variables, which are a major emphasis of the 2016 GAISE College Report.  The poem is part of a collection of 8 poems published with commentary in the January 2020 issue of Journal of Humanistic Mathematics.

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  • A poem written in 2019 by Larry Lesser from The University of Texas at El Paso to discuss systematic sampling.  Students should be familiar with the lyric being sampled from (though you could provide it to make sure) and verify that the systematic sample involved sampling every third word and starting with the lyric’s first word. Students could create their own poems with different systematic samples (or different text to sample from).  The poem is part of a collection of 8 poems published with commentary in the January 2020 issue of Journal of Humanistic Mathematics.

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  • A cartoon to illustrate the value of statistics in estimating the unemployment rate.  The cartoon was drawn in 2013 by British cartoonist John Landers based on an idea by Dennis Pearl from Ohio State University.  This item is part of the cartoons and readings from the “World Without Statistics” series that provided cartoons and readings on important applications of statistics created for celebration of 2013 International Year of Statistics.  The series may be found at https://online.stat.psu.edu/stat100/lesson/1/1.4

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  • A cartoon to illustrate the value of statistics in conducting sample surveys, such as those for predicting election results.  The cartoon was drawn in 2013 by British cartoonist John Landers based on an idea by Dennis Pearl from Ohio State University.  This item is part of the cartoons and readings from the “World Without Statistics” series that provided cartoons and readings on important applications of statistics created for celebration of 2013 International Year of Statistics.  The series may be found at https://online.stat.psu.edu/stat100/lesson/1/1.4

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  • A song discussing how a sample can be superior to a census.  The lyric was written in 2018 by Lawrence Lesser of The University of Texas at El Paso and parodies John Denver's 1974 #1 hit "Annie's Song".  The song was also published in the May 2019 Amstat News.

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  • A joke to use in discussing the poor representativeness of a convenience sample.  The joke was written in 2019 by Larry Lesser from The University of Texas at El Paso.

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  • A cartoon that can be a vehicle to discuss the nature of convenience samples and how they are likely to differ from probability-based samples. The cartoon was used in the January, 2018 CAUSE cartoon caption contest and the winning caption was submitted by Larry Lesser from The University of Texas at El Paso. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.

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  • A joke to aid in discussing Confirmation Bias (bias introduced in surveys because respondents tend to interpret things in a way that confirms their preexisting beliefs).  The joke was written by Larry Lesser from The Universisty of Texas at El Paso and Dennis Pearl from The Pennsylvania State University in October, 2018.

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  • This song covers some major real-world examples in the history of random sampling. The lyric was written in 2017 by Lawrence M Lesser from The University of Texas at El Paso and can be sung to the tune of theHarry Casey and Richard Finch song “(Shake, Shake, Shake) Shake Your Booty” that was a 1976 #1 hit for KC and the Sunshine Band.

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  • The emphasis in this course will be understanding statistical testing and estimation in the context of "omics" data so that you can appropriately design and analyze a high-throughput study. Since the measurement technologies are evolving rapidly, important objectives of the course are for students to gain a basic understanding of statistical principles and familiarity with flexible software tools so that you can continue to assess and use new statistical methodology as it is developed for new types of data.

    By the end of the course, you should be able to tailor the analysis of your data to your needs while maintaining statistical validity.  You should come out of the course with insight so that you can assess the validity of new statistical methodologies as they are introduced as well as understand appropriate statistical analyses for data types not discussed in the class. 

    Perfect for students and teachers wanting to learn/acquire materials for this topic.

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