A joke to use in discussing the meaning of the slope in a linear trend. The joke was written in May 2019 by Larry Lesser, The University of Texas at El Paso, and Dennis Pearl, Penn State University.
A joke to use in discussing the meaning of the slope in a linear trend. The joke was written in May 2019 by Larry Lesser, The University of Texas at El Paso, and Dennis Pearl, Penn State University.
A fun song about the average by American humorist and singer-songwriter Carla Ulbrich. The song was a finalist in the novelty category of the 2018 USA Songwriting Competition. The song is also available at www.theacousticguitarproject.com/artist/carla-ulbrich/ and more about the singer can be found at her website at www.carlau.com. For classroom use, you might ask which lines in "Totally Average Woman" refer to ways in which the woman in the song is at the mean, and which refer to ways in which she is at the median. Permission from singer is for free use for teaching in classroom and course websites with attribution. Commercial users must contact the copyright holder.
"By definition all scientists are data scientists. In my opinion, they are half hacker, half analyst, they use data to build products and find insights. It’s Columbus meet Columbo - starry eyed explorers and skeptical detectives," is a quote by Romanian American Data Scientist Monica Rogati. The quote is from an interview published in Forbes magazine on November 27, 2011.
A cartoon that can be helpful in introducing time series plots and their interpretation.The cartoon was used in the December 2018 CAUSE cartoon caption contest and the winning caption was written by Greg Baugher from Mercer University, Penfield College. 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 that can help in discussing how context matters in thinking about trend and "Seasonal" patterns in time series.The cartoon was used in the July 2018 CAUSE cartoon caption contest and the winning caption was written by Karsten Luebke from FOM University in Germany. The cartoon was drawnby British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.
A cartoon to start a discussion on the importance of appropriate axis labels. The cartoon was used in the September, 2017 CAUSE cartoon caption contest and the winning caption was submitted by Larry Lesser from The University of Texas at El Paso. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University. Another caption noticed the lack of any scale on the charts read simply "Label your axes!" and was submitted by Kyle Falbo of the College of the Redwoods. A different use of the cartoon can be made with the caption "Looks like a bad case of Regression to the Mean," which might be used in discussing that topic since the sicker patient in the cartoon is improving more.
A cartoon to initiate a class discussion about the idea of using statistical methods to navigate data and draw inferences. The cartoon was used in the July, 2017 CAUSE cartoon caption contest and the winning caption was submitted by Debmalya Nandy, a graduate student at Penn State University. An alternative caption that took an honorable mention in that month's contest was "Check that variances are equal before diving in with pooled variance!" written by Larry Lesser from The University of Texas at El Paso. 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 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.
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.
This case study starts by the simple comparison of the prices of houses with and without fireplaces and extends the analysis to examine other characteristics of the houses with fireplace that may affect the price as well. The intent is to show the danger of using simple group comparisons to answer a question that involves many variables. The lesson shows the R code for doing this analysis; however, the data and the model could be used with another statistical software.