A cartoon that can be used to discuss the importance of investigating and understanding the outliers in data sets. The cartoon was used in the January 2023 CAUSE cartoon caption contest and the winning caption was written by Amelia Williams, a student at University of Toronto. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
A cartoon that can be used to help start a class conversation about the importance of avoiding the removal of outliers without appropriate cause. The cartoon was used in the October 2021 CAUSE cartoon caption contest and the winning caption was written by Erik Svenneby a student at University of Colorado Boulder. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
A poem written in 2019 by Sabrina Little, a middle school student at the Mackintosh Academy in Boulder, CO. She entered it into the American Mathematical Society’s Math Poetry Contest contest for Colorado middle school, high school, and undergraduate students in connection with the 2020 Joint Mathematics Meetings in Denver. Sabina’s poem was judged the winner in the category for middle school students. The poem uses imagery which can enhance a lesson on line of fit and outliers. Sabrina Little read her poem at the 2020 Joint Mathematics Meetings (see 2:42 mark of the video posted at http://www.ams.org/programs/students/math-poetry).
A cartoon suitable for a course website that makes use of a boxplot to display an outlier and also uses the term "statistically significant" in its punch line. The cartoon is number 539 (February, 2009) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom and on course web sites under a creative commons attribution-non-commercial 2.5 license.
A cartoon useful in applied probability courses to discuss the nature of actuarial work and the importance of accounting for rare events.The cartoon was used in the April, 2018 CAUSE cartoon caption contest and the winning caption was written by Larry Lesser from The University of Texas at El Paso. An alternative caption that was a co-winner in that month’s contest was "Open your eyes to catch the significant events occurring at the tails," submitted by Debmalya Nandy, a graduate student at Penn State University. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
A cartoon that can be used in discussing the effect of outliers – especially on significance testing. The cartoon was used in the April, 2018 CAUSE cartoon caption contest and the winning caption was submitted by Debmalya Nandy, a graduate student at Penn State University. An alternative caption that was a co-winner in that month’s contest was "Actuaries write umbrella policies to cover freak accidents" written 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.
A cartoon that can be a vehicle to discuss how interesting discoveries are often made by investigating outliers.The cartoon was used in the March 2018 CAUSE cartoon caption contest and the winning caption was written by Jim Alloway from EMSQ Associates. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
A set of twenty statistics anagrams that might be used for an end of semester terminology review. This collection of anagrams appeared in the article "Even More Fun Learning Stats" by Lawrence M. Lesser in issue #49 (2007) of "Stats" magazine (pp.5-8,19, 27).
A sketch by Anastasia Mandel reinterpreting Cattle by a Lake by Sidney Richard Percy (1862) with the statistical caption "A multimodal distribution with small outliers." This is part of a collection of sketches by Anastasia Mandel 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.
Which is more robust against outliers: mean or median? This app demonstrates the (in)stability of these descriptive statistics as the value of an outlier and the number of data points change.