Resource Library

A song to be used in discussing how the correlation coefficient is invariant to linear transformations (or just reverses sign when values are multiplied by a negative number). 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 1980 song “Hit Me With Your Best Shot,” written by Eddie Schwartz and popularized by Pat Benatar. Also, an accompanying video may be found at https://www.youtube.com/watch?v=t-LtFLuA5VY

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 that may be used in discussing the correlation coefficient and the interpretation of positive versus negative values and their magnitude. 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 Carl Perkin’s 1955 rock and roll song Blue Suede Shoes. Also, an accompanying video may be found at
https://www.youtube.com/watch?v=RipAdV5jt0g

A song that may be used in discussing the meaning and interpretation of R^2; the coefficient of determination.  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 Christmas song Frosty the Snowman written by Walter Rollins and Steve Nelson and popularized by Gene Autry’s 1950 recording. Also, an accompanying video may be found at https://www.youtube.com/watch?v=0gdxJ0HhELg

 

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 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.

Many data sets useful for modeling bivariate relationships. The data sets are formatted for use in Fathom, but text versions are also available.

This collection of data can be used for many useful statistical analyses. Data and description are in a separate file and useful for SAS data analysis too. Data are categorized by analysis type, hence easy to pic relevant data sets accordingly. The data can be used for many analysis such as, Categorical data analysis, Polynomial Linear, Nonlinear, Logistic, Poisson, Negative Binomial Regression analysis, Response Surface Regression, Binary Response Regression, Time Series Data,1-Way ANOVA/ Independent Samples t-test, Multi-Factor ANOVA, and many other data analysis.