Fun

  • A short story that might be used in an out-of-class assignment to understand lifetime distributions. The story was written by Ben Marshall of FaithLife Financial in Waterloo Ontario, Canada. The story took first place in the 2007 Society of Actuaries 7th annual Speculative Fiction Contest.
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  • A short story that can be used in an out-of-class assignment in association with the study of probability rules, Bayes Theorem and expectations as they relate to games of chance. The story was written by Canadian Mathematician Robert Dawson from Saint Mary's University in Halifax, Nova Scotia and appeared in the Journal of Humanistic Mathematics (volume 7, issue 1, January 2017).
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    Average: 5 (1 vote)
  • A story that might be used as an out-of-class assignment associated with the study of population growth models (here the population is at equilibrium because both births and deaths are essentially non-existent). The story was written by Chris Fievoli from the Canadian Institute of Actuaries and won first place in the 8th Speculative Fiction Contest in 2009
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  • A short story that can be used as an out-of-class assignment associated with studying the probability of rare events and issues like those that arise in the birthday problem about how the chance that an event will happen to someone differs from the chance it will happen to you. The story was written in 1973 by Arkady and Boris Strugatsky and appeared in the short story compilation 'journey Across Three Worlds" (Mir Publishers, Moscow). The version here was translated from Russian to English by Gladys Evans.
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  • A science fiction short story that could be used in an out-of-class assignment associated with the topic of cyclic trends in time series. The story was written in 1952 by American science fiction writer Robert Heinlein and published in Galaxy Science Fiction magazine.
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  • A joke that might be used in a discussion of the problem of using a simple linear regression to extrapolate beyond the range of the data (where it is unlikely that the linear relationship would continue to hold). The joke was written by Dennis Pearl from Penn State University.
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    Average: 5 (1 vote)
  • A cartoon to be used for discussing the selection of the best explanatory variable in a regression model. The cartoon was used in the March 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Michele Balik-Meisner, a student at North Carolina State University. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. A second winning entry, by Michael Posner of Villanova University, may be found at www.causeweb.org/cause/resources/fun/cartoons/variable-wheel-ii Three honorable mentions that rose to the top of the judging in the March competition included "No no no! You randomize AFTER you select your research topic!" by Mickey Dunlap from University of Georgia; "This isn't what I meant by random variable!" by Larry Lesser from The University of Texas at El Paso; and "We find this method of finding 'significant' predictors to be quicker than using stepwise regression and it is even slightly more reproducible." by Greg Snow from Brigham Young University.

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  • A cartoon to be used for discussing the selection of the best explanatory variable in a regression model. The cartoon was used in the March 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Michael Posner, from Villanova University. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. A second winning entry, by Michele Balik-Meisner, a student at North Carolina State University, may be found at www.causeweb.org/cause/resources/fun/cartoons/variable-wheel-i Three honorable mentions that rose to the top of the judging in the March competition included "No no no! You randomize AFTER you select your research topic!" by Mickey Dunlap from University of Georgia; "This isn't what I meant by random variable!" by Larry Lesser from The University of Texas at El Paso; and "We find this method of finding 'significant' predictors to be quicker than using stepwise regression and it is even slightly more reproducible." by Greg Snow from Brigham Young University.

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  • A cartoon to be used for discussing the importance of efficiency in sampling. The cartoon was used in the April 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Mickey Dunlap from University of Georgia. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. Three honorable mentions that rose to the top of the judging in the April competition included "Better to ask for help BEFORE you're drowning in data!," written by Larry Lesser from University of Texas at El Paso; "I guess I should have asked for more details before signing up for this "Streaming Data" workshop," written by Chris Lacke from Rowan University; and "On reflection, random sampling WITH replacement might not have been appropriate in this scenario," written by Aaron Profitt from God's Bible School and College.

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    Average: 5 (1 vote)
  • A cartoon to be used for discussing the value of stratification in reducing the variability of population estimates (and the difficulty in doing so when the population weights are unknown).. The cartoon was used in the May 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Jim Alloway of EMSQ Associates. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. Two honorable mentions that rose to the top of the judging in the May competition may be found at https://www.causeweb.org/cause/resources/fun/cartoons/product-testing-ii written by Larry Lesser from University of Texas at El Paso and at https://www.causeweb.org/cause/resources/fun/cartoons/product-testing-iii written by John Bailer from Miami University.
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