CODAP provides an easy-to-use web-based data analysis platform, geared toward middle and high school students, and aimed at teachers and curriculum developers. CODAP can be incorporated across the curriculum to help students summarize, visualize and interpret data, advancing their skills to use data as evidence to support a claim.
A joke to be used in discussing the issue of regression to the mean. Note that the word "meme" is pronunced like "meem." The joke was written in 2017 by Larry Lesser (The University of Texas at El Paso) and Dennis Pearl (Penn State University).
A song for use in discussing the interpretation of the root mean squared error – or the standard deviation of the residuals. The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may to be sung to the tune of Michael Jackson’s 1982 hit song “Billy Jean.” Also, an accompanying video may be found at https://www.youtube.com/watch?v=RW-Rfn86CSQ
A song to aid in discussing the idea that the regression line is itself random and understanding the idea of the standard deviation of the estimated slope. The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may be sung to the tune of the 2015 hit song “Hello,” by English singer Adele. Also, an accompanying video may be found at
https://www.youtube.com/watch?v=nJgYTKsVYQw
A song to be used in discussing the idea that the point of averages (x-bar, y-bar) always lies on the regression line. The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may be sung to the tune of the 2014 hit “Shake it Off,” by Taylor Swift. Also, an accompanying video may be found at https://www.youtube.com/watch?v=XeVR2024dY0
A song that may be used in discussing the interpretation of the Y-intercept in a simple linear regression and the idea that the estimated Y-intercept may not make sense in the context of the problem (for example, taking impossible values or when X can never be zero) . The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may be sung to the tune of the 2013 song “Wrecking Ball,” by Miley Cyrus. Also, an accompanying video may be found at
https://www.youtube.com/watch?v=KNw4B71UsqY
A song that may be used in discussing the interpretation of the slope in a simple linear regression. The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may be sung to the tune of the theme song from the 1960’s television program The Addams Family written by composer Vic Mizzy. Also, an accompanying video may be found at https://www.youtube.com/watch?v=gGVj5p55REk
A song to be used in discussing the Regression Effect and the Regression Fallacy. The lyrics were written by Lawrence M. Lesser from The University of Texas at El Paso and may be sung to the tune of the 1977 song "Slip Slidin' Away" by Paul Simon. The song first appeared in the August 2017 Amstat News.
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.