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A game to help with the active learning of the kinds of applied scenarios that are appropriately modeled by distributions covered in an upper division undergraduate or masters level probability course. The game is part of the Distributome.org probability resources developed by Ivo Dinov (University of Michigan), Dennis Pearl (Penn State University), and Kyle Siegrist (University of Alabama).
A cartoon to be used for discussing the meaning of probability statements in the media such as when you hear there's a 25% chance of rain in the forecast. The cartoon was used in the July 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Michael Huberty from University of Minnesota., a student at Belgrade High School. The drawing was created by John Landers using an idea from Dennis Pearl. Other honorable mentions for captions that rose to the top of the judging that month included "A data set with seasonality" written by Larry Lesser from University of Texas at El Paso; "ANOVA â€“ Analysis of Varied Atmospheres," written by Deb Sedik from Bucks County Community College: and "Variability matters!" written by Debmalya Nandy, a student at Penn State University. (to use this cartoon with an alternate caption simply download and replace the caption using a bolded comic sans font)
A cartoon to be used in discussing the Elevator Paradox or other elevator related probability problems. The cartoon was used in the January 2017 CAUSE cartoon caption contest. The winning caption was written by Larry Lesser at The University of Texas at El Paso, while the drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl.
This is a web application framework for R, in which you can write and publish web apps without knowing HTML, Java, etc. You create two .R files: one that controls the user interface, and one that controls what the app does. The site contains examples of Shiny apps, a tutorial on how to get started, and information on how to have your apps hosted, if you don't have a server.
These slides from the 2014 ICOTS workshop describe a minimal set of R commands for Introductory Statistics. Also, it describes the best way to teach them to students. There are 61 slides that start with plotting, move through modeling, and finish with randomization.
"A Given A" is a song that Lawrence Mark Lesser from The University of Texas of El Paso adapted from his poem "P(A|A)" that was originally published in the January 2017 Journal of Humanistic Mathematics. In addition to providing a vehicle for general discussion (about pitfalls of post hoc analysis, multiple comparisons, or confusing the direction of causation or conditioning), the song may spark particularly lively discussion with the second verse's reference to the Bible Code, popularized by Michael Drosnin's so-named books and discussed in 1994 and 1999 papers in Statistical Science.
"Availability Heuristic" is a poem by Lawrence Mark Lesser from The University of Texas at El Paso. The poem was originally published in the January 2017 Journal of Humanistic Mathematics. Classroom discussion the poem may spark includes comparing and contrasting mathematical and statistical roles and language for generality, looking up and discussing the meaning of the title (a phenomenon identified by Kahneman and Tversky in 1973), exploring the"someone, somewhere" idea of Utts' Seeing Through Statistics, or discussing how many people have poor intuition with the birthday problem ("probability of at least one match in the room") because they confuse it with the birthdate ("probability at least one match with ME") problem (see letters in the summer 2014 Teaching Statistics).
This is an e-book tutorial for R. It is organized according to the topics usually taught in an Introductory Statistics course. Topics include: Qualitative Data; Quantitative Data; Numerical Measures; Probability Distributions; Interval Estimation; Hypothesis Testing; Type II Error; Inference about Two Populations; Goodness of Fit; Analysis of Variance; Non-parametric methods; Linear Regression; and Logistic Regression.
A quote to motivate discussion of how knowledge builds from a base. The quote is by Austrian-American Mathematician Hilda Geiringer (1893-1973) who used it in connection to her philosophy of probability and how it should build from a firm mathematical base but be connected to real world problems. The quote is contained in her 1964 preface to Mathematical Theory of Probability and Statistics by Richard von Mises (von Mises was her husband and she wrote and compiled the book from his notes after his death).