A humorous cartoon to initiate a conversation about scatterplots, the strength of linear relationships and the effect of outliers. The cartoon was drawn by American cartoonist Jon Carter in 2014.
A humorous cartoon to initiate a conversation about scatterplots, the strength of linear relationships and the effect of outliers. The cartoon was drawn by American cartoonist Jon Carter in 2014.
An interesting sestina poem to discuss measurement scales and can also be used while discussing spurious correlations if the teacher provides a guiding question such as “What part of the poem describes the relationship between quantitative variables, rather than just descriptions of quantitative variables? Are those relationships examples of 'Spurious Correlations' (per the title of the poem)? Explain briefly." If the students need further help, the instructor might suggest that they focus on the second to last stanza. The was written by Jules Nyquist, the founder of Jules' Poetry Playhouse, a place for poetry and play and published in the Journal of Humanistic Mathematics (2022) v. 12 #2 p.554.
A cartoon to aid in discussing confounding and correlative versus causal relationships, for example by asking students to suggest an alternate reason for the relationship besides the one jokingly illustrated in the cartoon. The cartoon was created by English cartoonist John Landers in December, 2021 based on an idea by Dennis Pearl (Penn State University) and Larry Lesser (The University of Texas at El Paso).
A video using dance to teach about concepts involved with correlation. This 2013 video is from the “Dancing Statistics” series developed by Lucy Irving from Middlesex University (UK) funded by a BPS Public Engagement grant and additional funding from IdeasTap. Full credits are within the video. The Dancing Statistics project is described at https://www.frontiersin.org/articles/10.3389/fpsyg.2015.00050/full
The video also comes with teaching notes for viewing by instructors who are logged into CAUSEweb.org.
A cartoon that can be used for discussing the traditional theme of "Correlation does not imply Causation" as well as what observational evidence does provide the most convincing evidence of a causal relationship. The cartoon was used in the June 2019 CAUSE cartoon caption contest. 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 to initiate discussions about how the correlation is a unitless number that does not change with changes in the units of the variables involved. The cartoon was created in February 2020 by British caetoonist John Landers based on an idea by Dennis Pearl (Penn State) and Larry Lesser (Univ of Texas at El Paso). An outline of a lesson plan for the use of the cartoon is given in a 2020 Teaching Statistics article by Dennis Pearl and Larry Lesser.
The Student Dust Counter is an instrument aboard the NASA New Horizons mission to Pluto, launched in 2006. As it travels to Pluto and beyond, SDC will provide information on the dust that strikes the spacecraft during its 14-year journey across the solar system. These observations will advance our understanding of the origin and evolution of our own solar system, as well as help scientists study planet formation in dust disks around other stars.
In this lesson, students explore the SDC data interface to establish any trends in the dust distribution in the solar system. Students record the number of dust particles, "hits," recorded by the instrument and the average mass of the particles in a given region.
The Neutral Buoyancy Laboratory allows astronauts an atmosphere resembling zero gravity (weightlessness) in order to train for missions involving spacewalks. In this activity, students will evaluate pressures experienced by astronauts and scuba divers who assist them while training in the NBL. This lesson addresses correlation, regression, residuals, inerpreting graphs, and making predictions.
NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.
Math and Science @ Work presents an activity for high school AP Statistics students. In this activity, students will look at data from an uncalibrated radar and a calibrated radar and determine how statistically significant the error is between the two different data sets.
NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: Pearson's residuals and rules for partitioning an I x J contingency tables as ways to determine association between variables.