Resource Library

A cartoon for use in discussions about the value of an active learning environment (Showing a traditional lecturer talking to no one and running out of blackboard space on a desert island). The cartoon is the work of Theresa McCracken and appears as #5924 on McHumor.com Free for non-profit use in statistics course such as in lectures and course websites.

A cartoon for use in discussions about how to critique quantitative evidence presented in the media. The cartoon is the work of Theresa McCracken and appears as #7203 on McHumor.com Free for non-profit use in statistics course such as in lectures and course websites.

A cartoon for use by teachers of night statistics classes. The cartoon is the work of Theresa McCracken and appears as #7178 on McHumor.com Free for non-profit use in statistics course such as in lectures and course websites.

July 13, 2010 T&L webinar presented by Webster West (Texas A&M University) and hosted by Jackie Miller(The Ohio State University). In introductory statistics courses, web-based applets are often used to visually conduct large simulation studies illustrating statistical concepts. However, it is difficult to determine what (if anything) students learn from repeatedly pressing a button when using applets. More advanced options such as writing/running computer code are typically considered to be much too advanced for most introductory courses. The web-based software package, StatCrunch, now offers simulation capabilities that strike a middle ground between these two extremes. The instructor/student needs only to perform a small number of steps using the menu driven interface with each step being key to understanding the underlying data structure. This talk will cover the steps required to study concepts such as the central limit theorem, confidence intervals, hypothesis testing and regression using StatCrunch.

This issue contains an article that provides an example of a paired samples test related to flying and gliding. It also includes an article about understanding confounding from lurking variables using graphs. Other articles include: a short description about what the t-tests actually tests, an interview with David Moore about why 30 is the "magic" number, a discussion about whether or not outliers should be deleted from a data set, a discussion of observational studies, and a simulation piece about random numbers from non-random arithmetic.

This issue contains an interview with Sallie Keller-McNulty and an article about which came first -- the chicken or the egg. Other articles include a discussion related to an AP Statistics example of seeing the trees for the forest (this focuses on understanding variability between groups and within groups), a discussion of how high r can go, a simulation piece focused on shrinking students, poisoned children, and bootsraps, and an example of a permutation test of the Challenger O-Ring data.

Every time man makes a new experiment he always learns more. He cannot learn less. is a quote of American inventor and author Richard Buckminster Fuller (1895-1983). The quote appears in his 1963 book "Operating Manual for Spaceship Earth".

A joke that might be used in discussing correlation - especially in health studies. The joke is adapted from a joke told by comedic magician Omar Covarrubias. The revised joke was written by Larry Lesser, University of Texas at El Paso, for use in the statistics classroom.

...the most misleading assumptions are the ones you don't even know you're making is a quote by English author Douglas Noel Adams (1952-2001) that can be used in teaching the importance of understanding the assumptions being made that underlie statistical inference. The quote is from the 1990 book "Last Chance to See" that was co-written with Mark Carwardine. It is part of a passage that Adams wrote about his experience watching a silverback gorilla in Zaire and trying to imagine what the animal was thinking about him.

January 11, 2011 T&L webinar presented by Rakhee Patel(University of California - Los Angeles, UCLA) and hosted by Jackie Miller (The Ohio State University). Since formal hypothesis testing and inference methods can be a challenging topic for students to tackle, introducing informal inference early in a course is a useful way of helping students understand the concept of a null distribution and how to make decisions about whether to reject it. We will present two computer labs, both using Fathom, that illustrate these concepts using permutation in a setting where students will be answering interesting investigative questions with real data.