Multivariate Quantitative Relationships

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

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  • 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 Michael Posner, from Villanova 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 Michele Balik-Meisner, a student at North Carolina State University, may be found at www.causeweb.org/cause/resources/fun/cartoons/variable-wheel-i 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.

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  • A joke to help in recalling the purpose of Correlation and Regression. The joke was written in 2017 by Dennis Pearl from Penn State University.
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  • A video for use in teaching about the dangers of extrapolating well beyond the range of the data in linear regression. The lyrics and Powerpoint components of the video were written by Michael Posner while the vocals were done by Reena Freedman of Villanova University and won first place in the video category of the 2017 A-mu-sing contest. The lyrics parody the song "How Far I'll Go" from the Disney animated feature film Moana (sung by Alessia Cara for the movie soundtrack).
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  • A cartoon suitable for use in discussing situations where the explanatory variable has essentially no predictive power (whether the variables have a statistically significant relationship or not). The cartoon is number 1725 (August, 2016) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom and on course web sites under a creative commons attribution-non-commercial 2.5 license.

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  • A cartoon to be used in discussing the interpretation of a regression equation (for example interpreting the intercept when it is well beyond the range of the data). The cartoon is #1823 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1823. Free for use in classrooms and course websites with acknowledgement (i.e. "Piled Higher and Deeper" by Jorge Cham, www.phdcomics.com)
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  • A cartoon to be used in discussing the least squares property of the regression line and the lexical ambiguity in the use of the word regression. The cartoon is #1921 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1921. Free for use in classrooms and course websites with acknowledgement (i.e. "Piled Higher and Deeper" by Jorge Cham, www.phdcomics.com)
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