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  • A song for teaching about the importance of penalized regression methods (ridge regression, LASSO, etc...). The song was written by Bradley Turnbull, Joe Usset, Sidd Roy, and Kyle White who, along with Kristin Linn and Jason Osborne, form the North Carolina State University Statistics Department Graduate Student band, "The Fifth Moment". The lyrics may be sung to the tune of the 2008 hit "Shake It" by the American pop group "Metro Station". "Shrink It" also won an honorable mention in the 2013 CAUSE A-Mu-sing competition. Available for free use in non-profit education settings.
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  • A song for teaching about the Cramer Rao Lower Bound for the variance of an unbiased estimate. The lyrics were written by Kyle White and Bradley Turnbull from North Carolina State University as a parody of the 2003 track "Jerk It Out" by the Swedish band "Caesars". The song won first prize in the song category in the 2013 CAUSE A-Mu-sing competition and is performed by "The Fifth Moment", an NCSU graduate student band (Kristin Linn, Jason Osborne, Siddharth Roy, Bradley Turnbull, Joseph Usset, and Kyle White). Free for use in non-profit education settings.
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  • A song to help students confront the "equiprobability bias". Lyrics and music were written by Lawrence Mark Lesser of University of Texas at El Paso. The song won an honorable mention in the 2013 CAUSE A-Mu-sing competition. Free for use in non-profit education settings.
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  • A song to teach about Benford's Law for the probability distribution of first digits in real data. The lyrics are copyright by Lawrence Mark Lesser as a parody of Harry Nilsson's "One" made popular in 1969 by "Three Dog Night". "One is the Likeliest Number" was first published in the Spring 2011 issue of "Teaching Statistics". Free for use in non-profit education settings. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.
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  • A cartoon to teach about the average and about positive versus negative skew. The cartoon was created by Diane L. Evans from Rose-Human Institute of Technology and won an honorable mention in the CAUSE 2013 A-Mu-sing contest.
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  • A video to teach about the central limit theorem and various issues in one-sample hypothesis testing. The lyrics and video were created by Scott Crawford from the University of Wyoming. The music is from the 1988 song "I'm Gonna Be (500 miles)" by the Scottish band The Proclaimers. The video took second place in the video category of the 2013 CAUSE A-Mu-sing competition. Free for non-profit use in classroom and course website applications.
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  • A video to teach about principles of Analysis of Variance. The lyrics and video were created by Scott Crawford from the University of Wyoming. The music is from the 1984 song "Hallelujah" by Canadian songwriter Leonard Cohen. The video took third place in the video category of the 2013 CAUSE A-Mu-sing competition. Free for non-profit use in classroom and course website applications.
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  • A video to dispel myths about Statistics and excite students early in a course. The lyrics and video were created by Scott Crawford from the University of Wyoming. The music is from the 2000 song "Where Are You, Christmas? " written by James Horner and Will Jennings for the movie "How the Grinch Stole Christmas". The video received an honorable mention in the video category of the 2013 CAUSE A-Mu-sing competition. Free for non-profit use in classroom and course website applications.
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  • A song providing an overview of Introductory Statistics with lyrics written by Michael Posner of Villanova University who also performs the song on the accompanying MP3 audio file. The song is a parody of the 2010 hit "Cooler Than Me" by Mike Posner. The song is also the sound track on the corresponding video at http://www.youtube.com/watch?v=4rKQtDb4VjU The video and song were the grand prize winner of the CAUSE 2013 A-Mu-sing competition. Free for use in nonprofit education applications.
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  • This simulation illustrates least squares regression and how the least squares solution minimizes the sum of the squared residuals. The applet demonstrates, in a visual manner, various concepts related to least squares regression. These include residuals, sum of squares, the mean line, how the line of best fit is determined, and how the line of least squares solution minimizes the sum of the squared residuals.
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